Overview

Brought to you by YData

Dataset statistics

Number of variables90
Number of observations103737
Missing cells4948218
Missing cells (%)53.0%
Total size in memory71.2 MiB
Average record size in memory720.0 B

Variable types

Text90

Dataset

DescriptionNCSM Herpetology Collection 0001383-250121130708018
URLhttps://doi.org/10.15468/enivwl

Alerts

accessRights has constant value "not-for-profit use only" Constant
bibliographicCitation has constant value "NCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection" Constant
modified has constant value "2020-01-07 12:35:09" Constant
references has constant value "https://collections.naturalsciences.org/herpetology/specimen/1" Constant
rightsHolder has constant value "Noth Carolina Museum of Natural Sciences" Constant
institutionID has constant value "NCSM" Constant
datasetID has constant value "HerpDWC" Constant
institutionCode has constant value "NCSM" Constant
collectionCode has constant value "Herp" Constant
datasetName has constant value "NCSM Herpetology Collection" Constant
ownerInstitutionCode has constant value "NCSM" Constant
basisOfRecord has constant value "PreservedSpecimen" Constant
informationWithheld has constant value "Detailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information." Constant
parentEventID has constant value "34.1384" Constant
eventDate has constant value "WGS84" Constant
eventRemarks has constant value "Personal Communication" Constant
locationRemarks has constant value "34.8546" Constant
verbatimCoordinates has constant value "1954" Constant
verbatimLatitude has constant value "04" Constant
verbatimLongitude has constant value "7" Constant
footprintSRS has constant value "Bufo quercicus" Constant
georeferenceProtocol has constant value "Personal Communication" Constant
latestPeriodOrHighestSystem has constant value "Bufonidae" Constant
latestEpochOrHighestSeries has constant value "Saluda" Constant
lowestBiostratigraphicZone has constant value "Desmognathus" Constant
group has constant value "quercicus" Constant
bed has constant value "specificEpithet" Constant
identificationID has constant value "specificEpithet" Constant
identificationQualifier has constant value "Oak Toad" Constant
identifiedByID has constant value "34.0015" Constant
dateIdentified has constant value "-81.7721" Constant
identificationReferences has constant value "WGS84" Constant
taxonConceptID has constant value "Pseudacris brimleyi" Constant
nameAccordingTo has constant value "DeLorme Topo USA 6.0" Constant
higherClassification has constant value "Animalia" Constant
superfamily has constant value "Hylidae" Constant
subtribe has constant value "Pseudacris" Constant
infragenericEpithet has constant value "brimleyi" Constant
cultivarEpithet has constant value "specificEpithet" Constant
scientificNameAuthorship has constant value "Brimley's Chorus Frog" Constant
informationWithheld has 98502 (95.0%) missing values Missing
sex has 74008 (71.3%) missing values Missing
lifeStage has 73653 (71.0%) missing values Missing
otherCatalogNumbers has 44162 (42.6%) missing values Missing
occurrenceRemarks has 53843 (51.9%) missing values Missing
organismID has 103735 (> 99.9%) missing values Missing
parentEventID has 103736 (> 99.9%) missing values Missing
eventType has 103734 (> 99.9%) missing values Missing
eventDate has 103735 (> 99.9%) missing values Missing
eventTime has 103735 (> 99.9%) missing values Missing
year has 4161 (4.0%) missing values Missing
month has 6115 (5.9%) missing values Missing
day has 10618 (10.2%) missing values Missing
eventRemarks has 103736 (> 99.9%) missing values Missing
locationID has 103735 (> 99.9%) missing values Missing
county has 6969 (6.7%) missing values Missing
municipality has 102849 (99.1%) missing values Missing
locality has 6009 (5.8%) missing values Missing
verbatimLocality has 51237 (49.4%) missing values Missing
locationRemarks has 103734 (> 99.9%) missing values Missing
decimalLatitude has 6514 (6.3%) missing values Missing
decimalLongitude has 6513 (6.3%) missing values Missing
geodeticDatum has 2328 (2.2%) missing values Missing
coordinateUncertaintyInMeters has 22047 (21.3%) missing values Missing
verbatimCoordinates has 103736 (> 99.9%) missing values Missing
verbatimLatitude has 103736 (> 99.9%) missing values Missing
verbatimLongitude has 103736 (> 99.9%) missing values Missing
footprintSRS has 103736 (> 99.9%) missing values Missing
footprintSpatialFit has 103735 (> 99.9%) missing values Missing
georeferenceProtocol has 103734 (> 99.9%) missing values Missing
georeferenceSources has 1367 (1.3%) missing values Missing
earliestEonOrLowestEonothem has 103735 (> 99.9%) missing values Missing
latestEonOrHighestEonothem has 103734 (> 99.9%) missing values Missing
earliestEraOrLowestErathem has 103734 (> 99.9%) missing values Missing
latestEraOrHighestErathem has 103735 (> 99.9%) missing values Missing
earliestPeriodOrLowestSystem has 103735 (> 99.9%) missing values Missing
latestPeriodOrHighestSystem has 103736 (> 99.9%) missing values Missing
earliestEpochOrLowestSeries has 103735 (> 99.9%) missing values Missing
latestEpochOrHighestSeries has 103736 (> 99.9%) missing values Missing
latestAgeOrHighestStage has 103735 (> 99.9%) missing values Missing
lowestBiostratigraphicZone has 103735 (> 99.9%) missing values Missing
group has 103736 (> 99.9%) missing values Missing
formation has 103735 (> 99.9%) missing values Missing
bed has 103736 (> 99.9%) missing values Missing
identificationID has 103735 (> 99.9%) missing values Missing
identificationQualifier has 103736 (> 99.9%) missing values Missing
typeStatus has 103407 (99.7%) missing values Missing
identifiedByID has 103736 (> 99.9%) missing values Missing
dateIdentified has 103736 (> 99.9%) missing values Missing
identificationReferences has 103736 (> 99.9%) missing values Missing
taxonConceptID has 103734 (> 99.9%) missing values Missing
nameAccordingTo has 103736 (> 99.9%) missing values Missing
higherClassification has 103734 (> 99.9%) missing values Missing
class has 5037 (4.9%) missing values Missing
order has 3728 (3.6%) missing values Missing
superfamily has 103734 (> 99.9%) missing values Missing
family has 3728 (3.6%) missing values Missing
subtribe has 103734 (> 99.9%) missing values Missing
infragenericEpithet has 103734 (> 99.9%) missing values Missing
infraspecificEpithet has 100055 (96.5%) missing values Missing
cultivarEpithet has 103734 (> 99.9%) missing values Missing
scientificNameAuthorship has 103734 (> 99.9%) missing values Missing
vernacularName has 10563 (10.2%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique

Reproduction

Analysis started2025-01-23 23:14:47.691837
Analysis finished2025-01-23 23:14:53.018829
Duration5.33 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct103737
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:53.214578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.603979294
Min length9

Characters and Unicode

Total characters996288
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103737 ?
Unique (%)100.0%

Sample

1st row1229584545
2nd row895439767
3rd row1844171852
4th row3712190566
5th row3991142329
ValueCountFrequency (%)
1229584545 1
 
< 0.1%
2542891747 1
 
< 0.1%
3712190566 1
 
< 0.1%
3991142329 1
 
< 0.1%
895446198 1
 
< 0.1%
895427092 1
 
< 0.1%
895418400 1
 
< 0.1%
3111565119 1
 
< 0.1%
895447984 1
 
< 0.1%
895431421 1
 
< 0.1%
Other values (103727) 103727
> 99.9%
2025-01-23T18:14:53.514620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 146548
14.7%
1 143486
14.4%
9 125783
12.6%
5 119003
11.9%
8 114668
11.5%
3 89835
9.0%
2 84535
8.5%
6 64582
6.5%
7 56478
 
5.7%
0 51370
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 996288
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 146548
14.7%
1 143486
14.4%
9 125783
12.6%
5 119003
11.9%
8 114668
11.5%
3 89835
9.0%
2 84535
8.5%
6 64582
6.5%
7 56478
 
5.7%
0 51370
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 996288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 146548
14.7%
1 143486
14.4%
9 125783
12.6%
5 119003
11.9%
8 114668
11.5%
3 89835
9.0%
2 84535
8.5%
6 64582
6.5%
7 56478
 
5.7%
0 51370
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 996288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 146548
14.7%
1 143486
14.4%
9 125783
12.6%
5 119003
11.9%
8 114668
11.5%
3 89835
9.0%
2 84535
8.5%
6 64582
6.5%
7 56478
 
5.7%
0 51370
 
5.2%

accessRights
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:53.579654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters2385951
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownot-for-profit use only
2nd rownot-for-profit use only
3rd rownot-for-profit use only
4th rownot-for-profit use only
5th rownot-for-profit use only
ValueCountFrequency (%)
not-for-profit 103737
33.3%
use 103737
33.3%
only 103737
33.3%
2025-01-23T18:14:53.683251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 414948
17.4%
n 207474
8.7%
t 207474
8.7%
- 207474
8.7%
f 207474
8.7%
r 207474
8.7%
207474
8.7%
p 103737
 
4.3%
i 103737
 
4.3%
u 103737
 
4.3%
Other values (4) 414948
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1971003
82.6%
Dash Punctuation 207474
 
8.7%
Space Separator 207474
 
8.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 414948
21.1%
n 207474
10.5%
t 207474
10.5%
f 207474
10.5%
r 207474
10.5%
p 103737
 
5.3%
i 103737
 
5.3%
u 103737
 
5.3%
s 103737
 
5.3%
e 103737
 
5.3%
Other values (2) 207474
10.5%
Dash Punctuation
ValueCountFrequency (%)
- 207474
100.0%
Space Separator
ValueCountFrequency (%)
207474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1971003
82.6%
Common 414948
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 414948
21.1%
n 207474
10.5%
t 207474
10.5%
f 207474
10.5%
r 207474
10.5%
p 103737
 
5.3%
i 103737
 
5.3%
u 103737
 
5.3%
s 103737
 
5.3%
e 103737
 
5.3%
Other values (2) 207474
10.5%
Common
ValueCountFrequency (%)
- 207474
50.0%
207474
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2385951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 414948
17.4%
n 207474
8.7%
t 207474
8.7%
- 207474
8.7%
f 207474
8.7%
r 207474
8.7%
207474
8.7%
p 103737
 
4.3%
i 103737
 
4.3%
u 103737
 
4.3%
Other values (4) 414948
17.4%

bibliographicCitation
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:53.747018image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters7572801
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection
2nd rowNCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection
3rd rowNCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection
4th rowNCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection
5th rowNCSM 1 - North Carolina Museum of Natural Sciences Herpetology Collection
ValueCountFrequency (%)
ncsm 103737
9.1%
1 103737
9.1%
103737
9.1%
north 103737
9.1%
carolina 103737
9.1%
museum 103737
9.1%
of 103737
9.1%
natural 103737
9.1%
sciences 103737
9.1%
herpetology 103737
9.1%
2025-01-23T18:14:53.871358image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1037370
13.7%
o 726159
 
9.6%
e 622422
 
8.2%
l 518685
 
6.8%
r 414948
 
5.5%
t 414948
 
5.5%
a 414948
 
5.5%
C 311211
 
4.1%
c 311211
 
4.1%
u 311211
 
4.1%
Other values (15) 2489688
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5186850
68.5%
Uppercase Letter 1141107
 
15.1%
Space Separator 1037370
 
13.7%
Dash Punctuation 103737
 
1.4%
Decimal Number 103737
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 726159
14.0%
e 622422
12.0%
l 518685
10.0%
r 414948
8.0%
t 414948
8.0%
a 414948
8.0%
c 311211
 
6.0%
u 311211
 
6.0%
n 311211
 
6.0%
i 311211
 
6.0%
Other values (7) 829896
16.0%
Uppercase Letter
ValueCountFrequency (%)
C 311211
27.3%
N 311211
27.3%
M 207474
18.2%
S 207474
18.2%
H 103737
 
9.1%
Space Separator
ValueCountFrequency (%)
1037370
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103737
100.0%
Decimal Number
ValueCountFrequency (%)
1 103737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6327957
83.6%
Common 1244844
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 726159
 
11.5%
e 622422
 
9.8%
l 518685
 
8.2%
r 414948
 
6.6%
t 414948
 
6.6%
a 414948
 
6.6%
C 311211
 
4.9%
c 311211
 
4.9%
u 311211
 
4.9%
n 311211
 
4.9%
Other values (12) 1971003
31.1%
Common
ValueCountFrequency (%)
1037370
83.3%
- 103737
 
8.3%
1 103737
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7572801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1037370
13.7%
o 726159
 
9.6%
e 622422
 
8.2%
l 518685
 
6.8%
r 414948
 
5.5%
t 414948
 
5.5%
a 414948
 
5.5%
C 311211
 
4.1%
c 311211
 
4.1%
u 311211
 
4.1%
Other values (15) 2489688
32.9%

modified
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:53.921676image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1971003
Distinct characters10
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01-07 12:35:09
2nd row2020-01-07 12:35:09
3rd row2020-01-07 12:35:09
4th row2020-01-07 12:35:09
5th row2020-01-07 12:35:09
ValueCountFrequency (%)
2020-01-07 103737
50.0%
12:35:09 103737
50.0%
2025-01-23T18:14:54.028241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 518685
26.3%
2 311211
15.8%
- 207474
 
10.5%
1 207474
 
10.5%
: 207474
 
10.5%
7 103737
 
5.3%
103737
 
5.3%
3 103737
 
5.3%
5 103737
 
5.3%
9 103737
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1452318
73.7%
Dash Punctuation 207474
 
10.5%
Other Punctuation 207474
 
10.5%
Space Separator 103737
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 518685
35.7%
2 311211
21.4%
1 207474
 
14.3%
7 103737
 
7.1%
3 103737
 
7.1%
5 103737
 
7.1%
9 103737
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 207474
100.0%
Other Punctuation
ValueCountFrequency (%)
: 207474
100.0%
Space Separator
ValueCountFrequency (%)
103737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1971003
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 518685
26.3%
2 311211
15.8%
- 207474
 
10.5%
1 207474
 
10.5%
: 207474
 
10.5%
7 103737
 
5.3%
103737
 
5.3%
3 103737
 
5.3%
5 103737
 
5.3%
9 103737
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1971003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 518685
26.3%
2 311211
15.8%
- 207474
 
10.5%
1 207474
 
10.5%
: 207474
 
10.5%
7 103737
 
5.3%
103737
 
5.3%
3 103737
 
5.3%
5 103737
 
5.3%
9 103737
 
5.3%

references
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.089931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length62
Mean length62
Min length62

Characters and Unicode

Total characters6431694
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://collections.naturalsciences.org/herpetology/specimen/1
2nd rowhttps://collections.naturalsciences.org/herpetology/specimen/1
3rd rowhttps://collections.naturalsciences.org/herpetology/specimen/1
4th rowhttps://collections.naturalsciences.org/herpetology/specimen/1
5th rowhttps://collections.naturalsciences.org/herpetology/specimen/1
ValueCountFrequency (%)
https://collections.naturalsciences.org/herpetology/specimen/1 103737
100.0%
2025-01-23T18:14:54.203811image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 726159
11.3%
s 518685
 
8.1%
/ 518685
 
8.1%
c 518685
 
8.1%
o 518685
 
8.1%
t 518685
 
8.1%
l 414948
 
6.5%
n 414948
 
6.5%
i 311211
 
4.8%
p 311211
 
4.8%
Other values (10) 1659792
25.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5498061
85.5%
Other Punctuation 829896
 
12.9%
Decimal Number 103737
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 726159
13.2%
s 518685
9.4%
c 518685
9.4%
o 518685
9.4%
t 518685
9.4%
l 414948
7.5%
n 414948
7.5%
i 311211
 
5.7%
p 311211
 
5.7%
r 311211
 
5.7%
Other values (6) 933633
17.0%
Other Punctuation
ValueCountFrequency (%)
/ 518685
62.5%
. 207474
 
25.0%
: 103737
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 103737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5498061
85.5%
Common 933633
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 726159
13.2%
s 518685
9.4%
c 518685
9.4%
o 518685
9.4%
t 518685
9.4%
l 414948
7.5%
n 414948
7.5%
i 311211
 
5.7%
p 311211
 
5.7%
r 311211
 
5.7%
Other values (6) 933633
17.0%
Common
ValueCountFrequency (%)
/ 518685
55.6%
. 207474
 
22.2%
: 103737
 
11.1%
1 103737
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6431694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 726159
11.3%
s 518685
 
8.1%
/ 518685
 
8.1%
c 518685
 
8.1%
o 518685
 
8.1%
t 518685
 
8.1%
l 414948
 
6.5%
n 414948
 
6.5%
i 311211
 
4.8%
p 311211
 
4.8%
Other values (10) 1659792
25.8%

rightsHolder
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.257411image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length40
Mean length40
Min length40

Characters and Unicode

Total characters4149480
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNoth Carolina Museum of Natural Sciences
2nd rowNoth Carolina Museum of Natural Sciences
3rd rowNoth Carolina Museum of Natural Sciences
4th rowNoth Carolina Museum of Natural Sciences
5th rowNoth Carolina Museum of Natural Sciences
ValueCountFrequency (%)
noth 103737
16.7%
carolina 103737
16.7%
museum 103737
16.7%
of 103737
16.7%
natural 103737
16.7%
sciences 103737
16.7%
2025-01-23T18:14:54.366824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
518685
12.5%
a 414948
 
10.0%
o 311211
 
7.5%
e 311211
 
7.5%
u 311211
 
7.5%
N 207474
 
5.0%
s 207474
 
5.0%
n 207474
 
5.0%
i 207474
 
5.0%
l 207474
 
5.0%
Other values (9) 1244844
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3112110
75.0%
Space Separator 518685
 
12.5%
Uppercase Letter 518685
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 414948
13.3%
o 311211
10.0%
e 311211
10.0%
u 311211
10.0%
s 207474
 
6.7%
n 207474
 
6.7%
i 207474
 
6.7%
l 207474
 
6.7%
r 207474
 
6.7%
t 207474
 
6.7%
Other values (4) 518685
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 207474
40.0%
M 103737
20.0%
C 103737
20.0%
S 103737
20.0%
Space Separator
ValueCountFrequency (%)
518685
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3630795
87.5%
Common 518685
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 414948
 
11.4%
o 311211
 
8.6%
e 311211
 
8.6%
u 311211
 
8.6%
N 207474
 
5.7%
s 207474
 
5.7%
n 207474
 
5.7%
i 207474
 
5.7%
l 207474
 
5.7%
r 207474
 
5.7%
Other values (8) 1037370
28.6%
Common
ValueCountFrequency (%)
518685
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4149480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
518685
12.5%
a 414948
 
10.0%
o 311211
 
7.5%
e 311211
 
7.5%
u 311211
 
7.5%
N 207474
 
5.0%
s 207474
 
5.0%
n 207474
 
5.0%
i 207474
 
5.0%
l 207474
 
5.0%
Other values (9) 1244844
30.0%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.410701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters414948
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNCSM
2nd rowNCSM
3rd rowNCSM
4th rowNCSM
5th rowNCSM
ValueCountFrequency (%)
ncsm 103737
100.0%
2025-01-23T18:14:54.506787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 414948
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414948
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 414948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

datasetID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.548347image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters726159
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHerpDWC
2nd rowHerpDWC
3rd rowHerpDWC
4th rowHerpDWC
5th rowHerpDWC
ValueCountFrequency (%)
herpdwc 103737
100.0%
2025-01-23T18:14:54.644260image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 103737
14.3%
e 103737
14.3%
r 103737
14.3%
p 103737
14.3%
D 103737
14.3%
W 103737
14.3%
C 103737
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 414948
57.1%
Lowercase Letter 311211
42.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 103737
25.0%
D 103737
25.0%
W 103737
25.0%
C 103737
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 103737
33.3%
r 103737
33.3%
p 103737
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 726159
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 103737
14.3%
e 103737
14.3%
r 103737
14.3%
p 103737
14.3%
D 103737
14.3%
W 103737
14.3%
C 103737
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 726159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 103737
14.3%
e 103737
14.3%
r 103737
14.3%
p 103737
14.3%
D 103737
14.3%
W 103737
14.3%
C 103737
14.3%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.687815image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters414948
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNCSM
2nd rowNCSM
3rd rowNCSM
4th rowNCSM
5th rowNCSM
ValueCountFrequency (%)
ncsm 103737
100.0%
2025-01-23T18:14:54.786055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 414948
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414948
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 414948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.828380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters414948
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHerp
2nd rowHerp
3rd rowHerp
4th rowHerp
5th rowHerp
ValueCountFrequency (%)
herp 103737
100.0%
2025-01-23T18:14:54.924401image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 103737
25.0%
e 103737
25.0%
r 103737
25.0%
p 103737
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 311211
75.0%
Uppercase Letter 103737
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 103737
33.3%
r 103737
33.3%
p 103737
33.3%
Uppercase Letter
ValueCountFrequency (%)
H 103737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414948
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 103737
25.0%
e 103737
25.0%
r 103737
25.0%
p 103737
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 414948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 103737
25.0%
e 103737
25.0%
r 103737
25.0%
p 103737
25.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:54.972997image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters2800899
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNCSM Herpetology Collection
2nd rowNCSM Herpetology Collection
3rd rowNCSM Herpetology Collection
4th rowNCSM Herpetology Collection
5th rowNCSM Herpetology Collection
ValueCountFrequency (%)
ncsm 103737
33.3%
herpetology 103737
33.3%
collection 103737
33.3%
2025-01-23T18:14:55.079497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 414948
14.8%
l 311211
11.1%
e 311211
11.1%
207474
 
7.4%
C 207474
 
7.4%
t 207474
 
7.4%
N 103737
 
3.7%
i 103737
 
3.7%
c 103737
 
3.7%
y 103737
 
3.7%
Other values (7) 726159
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1971003
70.4%
Uppercase Letter 622422
 
22.2%
Space Separator 207474
 
7.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 414948
21.1%
l 311211
15.8%
e 311211
15.8%
t 207474
10.5%
i 103737
 
5.3%
c 103737
 
5.3%
y 103737
 
5.3%
g 103737
 
5.3%
p 103737
 
5.3%
r 103737
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 207474
33.3%
N 103737
16.7%
H 103737
16.7%
M 103737
16.7%
S 103737
16.7%
Space Separator
ValueCountFrequency (%)
207474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2593425
92.6%
Common 207474
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 414948
16.0%
l 311211
12.0%
e 311211
12.0%
C 207474
 
8.0%
t 207474
 
8.0%
N 103737
 
4.0%
i 103737
 
4.0%
c 103737
 
4.0%
y 103737
 
4.0%
g 103737
 
4.0%
Other values (6) 622422
24.0%
Common
ValueCountFrequency (%)
207474
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2800899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 414948
14.8%
l 311211
11.1%
e 311211
11.1%
207474
 
7.4%
C 207474
 
7.4%
t 207474
 
7.4%
N 103737
 
3.7%
i 103737
 
3.7%
c 103737
 
3.7%
y 103737
 
3.7%
Other values (7) 726159
25.9%

ownerInstitutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:55.126453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters414948
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNCSM
2nd rowNCSM
3rd rowNCSM
4th rowNCSM
5th rowNCSM
ValueCountFrequency (%)
ncsm 103737
100.0%
2025-01-23T18:14:55.225690image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 414948
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 414948
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 414948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 103737
25.0%
C 103737
25.0%
S 103737
25.0%
M 103737
25.0%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:55.276226image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters1763529
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 103737
100.0%
2025-01-23T18:14:55.380211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 518685
29.4%
r 207474
 
11.8%
P 103737
 
5.9%
s 103737
 
5.9%
v 103737
 
5.9%
d 103737
 
5.9%
S 103737
 
5.9%
p 103737
 
5.9%
c 103737
 
5.9%
i 103737
 
5.9%
Other values (2) 207474
 
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1556055
88.2%
Uppercase Letter 207474
 
11.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 518685
33.3%
r 207474
 
13.3%
s 103737
 
6.7%
v 103737
 
6.7%
d 103737
 
6.7%
p 103737
 
6.7%
c 103737
 
6.7%
i 103737
 
6.7%
m 103737
 
6.7%
n 103737
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
P 103737
50.0%
S 103737
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1763529
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 518685
29.4%
r 207474
 
11.8%
P 103737
 
5.9%
s 103737
 
5.9%
v 103737
 
5.9%
d 103737
 
5.9%
S 103737
 
5.9%
p 103737
 
5.9%
c 103737
 
5.9%
i 103737
 
5.9%
Other values (2) 207474
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1763529
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 518685
29.4%
r 207474
 
11.8%
P 103737
 
5.9%
s 103737
 
5.9%
v 103737
 
5.9%
d 103737
 
5.9%
S 103737
 
5.9%
p 103737
 
5.9%
c 103737
 
5.9%
i 103737
 
5.9%
Other values (2) 207474
 
11.8%

informationWithheld
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing98502
Missing (%)95.0%
Memory size810.6 KiB
2025-01-23T18:14:55.449474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length197
Median length197
Mean length197
Min length197

Characters and Unicode

Total characters1031295
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDetailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information.
2nd rowDetailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information.
3rd rowDetailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information.
4th rowDetailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information.
5th rowDetailed geographic information (e.g., latitude and longitude coordinates) associated with a specimen are not provided for species deemed sensitive. Please contact the curator for more information.
ValueCountFrequency (%)
information 10470
 
7.7%
for 10470
 
7.7%
detailed 5235
 
3.8%
not 5235
 
3.8%
curator 5235
 
3.8%
the 5235
 
3.8%
contact 5235
 
3.8%
please 5235
 
3.8%
sensitive 5235
 
3.8%
deemed 5235
 
3.8%
Other values (14) 73290
53.8%
2025-01-23T18:14:55.579501image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130875
12.7%
e 120405
11.7%
i 83760
 
8.1%
o 83760
 
8.1%
t 78525
 
7.6%
a 73290
 
7.1%
r 57585
 
5.6%
n 57585
 
5.6%
d 52350
 
5.1%
s 47115
 
4.6%
Other values (16) 246045
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 853305
82.7%
Space Separator 130875
 
12.7%
Other Punctuation 26175
 
2.5%
Uppercase Letter 10470
 
1.0%
Close Punctuation 5235
 
0.5%
Open Punctuation 5235
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 120405
14.1%
i 83760
9.8%
o 83760
9.8%
t 78525
9.2%
a 73290
8.6%
r 57585
 
6.7%
n 57585
 
6.7%
d 52350
 
6.1%
s 47115
 
5.5%
c 41880
 
4.9%
Other values (9) 157050
18.4%
Other Punctuation
ValueCountFrequency (%)
. 20940
80.0%
, 5235
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
D 5235
50.0%
P 5235
50.0%
Space Separator
ValueCountFrequency (%)
130875
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5235
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 863775
83.8%
Common 167520
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 120405
13.9%
i 83760
9.7%
o 83760
9.7%
t 78525
9.1%
a 73290
8.5%
r 57585
 
6.7%
n 57585
 
6.7%
d 52350
 
6.1%
s 47115
 
5.5%
c 41880
 
4.8%
Other values (11) 167520
19.4%
Common
ValueCountFrequency (%)
130875
78.1%
. 20940
 
12.5%
) 5235
 
3.1%
, 5235
 
3.1%
( 5235
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1031295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
130875
12.7%
e 120405
11.7%
i 83760
 
8.1%
o 83760
 
8.1%
t 78525
 
7.6%
a 73290
 
7.1%
r 57585
 
5.6%
n 57585
 
5.6%
d 52350
 
5.1%
s 47115
 
4.6%
Other values (16) 246045
23.9%

occurrenceID
Text

Unique 

Distinct103737
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:55.696346image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters3734532
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103737 ?
Unique (%)100.0%

Sample

1st rowb82b4cf4-48a0-11ec-80ba-06f21c000156
2nd rowb738c682-48a0-11ec-80ba-06f21c000156
3rd rowb8667664-48a0-11ec-80ba-06f21c000156
4th rowa2531ed7-3516-11ed-80ba-06f21c000156
5th rowaab42f05-7cbd-11ed-9014-06f21c000156
ValueCountFrequency (%)
b82b4cf4-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b8aa2641-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
a2531ed7-3516-11ed-80ba-06f21c000156 1
 
< 0.1%
aab42f05-7cbd-11ed-9014-06f21c000156 1
 
< 0.1%
b771ce62-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b69ec835-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b64075a7-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b7bca4ed-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b781602d-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
b6e1e0f3-48a0-11ec-80ba-06f21c000156 1
 
< 0.1%
Other values (103727) 103727
> 99.9%
2025-01-23T18:14:55.873481image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 632790
16.9%
1 470619
12.6%
- 414948
11.1%
6 298793
8.0%
8 251699
 
6.7%
a 240153
 
6.4%
c 234660
 
6.3%
b 228953
 
6.1%
5 164969
 
4.4%
2 151174
 
4.0%
Other values (7) 645774
17.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2270873
60.8%
Lowercase Letter 1048711
28.1%
Dash Punctuation 414948
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 632790
27.9%
1 470619
20.7%
6 298793
13.2%
8 251699
 
11.1%
5 164969
 
7.3%
2 151174
 
6.7%
4 125433
 
5.5%
7 74039
 
3.3%
3 52197
 
2.3%
9 49160
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
a 240153
22.9%
c 234660
22.4%
b 228953
21.8%
e 143055
13.6%
f 137066
13.1%
d 64824
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 414948
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2685821
71.9%
Latin 1048711
 
28.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 632790
23.6%
1 470619
17.5%
- 414948
15.4%
6 298793
11.1%
8 251699
 
9.4%
5 164969
 
6.1%
2 151174
 
5.6%
4 125433
 
4.7%
7 74039
 
2.8%
3 52197
 
1.9%
Latin
ValueCountFrequency (%)
a 240153
22.9%
c 234660
22.4%
b 228953
21.8%
e 143055
13.6%
f 137066
13.1%
d 64824
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3734532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 632790
16.9%
1 470619
12.6%
- 414948
11.1%
6 298793
8.0%
8 251699
 
6.7%
a 240153
 
6.4%
c 234660
 
6.3%
b 228953
 
6.1%
5 164969
 
4.4%
2 151174
 
4.0%
Other values (7) 645774
17.3%

catalogNumber
Text

Unique 

Distinct103737
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:56.108571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.991401332
Min length1

Characters and Unicode

Total characters517793
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103737 ?
Unique (%)100.0%

Sample

1st row86627
2nd row62585
3rd row92192
4th row18073
5th row25999
ValueCountFrequency (%)
86627 1
 
< 0.1%
102220 1
 
< 0.1%
18073 1
 
< 0.1%
25999 1
 
< 0.1%
69924 1
 
< 0.1%
24464 1
 
< 0.1%
4769 1
 
< 0.1%
78725 1
 
< 0.1%
71760 1
 
< 0.1%
53915 1
 
< 0.1%
Other values (103727) 103727
> 99.9%
2025-01-23T18:14:56.406314image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61980
12.0%
6 51518
9.9%
2 51216
9.9%
8 51054
9.9%
7 51021
9.9%
9 50836
9.8%
3 50325
9.7%
5 50085
9.7%
4 49933
9.6%
0 49825
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 517793
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61980
12.0%
6 51518
9.9%
2 51216
9.9%
8 51054
9.9%
7 51021
9.9%
9 50836
9.8%
3 50325
9.7%
5 50085
9.7%
4 49933
9.6%
0 49825
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 517793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61980
12.0%
6 51518
9.9%
2 51216
9.9%
8 51054
9.9%
7 51021
9.9%
9 50836
9.8%
3 50325
9.7%
5 50085
9.7%
4 49933
9.6%
0 49825
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61980
12.0%
6 51518
9.9%
2 51216
9.9%
8 51054
9.9%
7 51021
9.9%
9 50836
9.8%
3 50325
9.7%
5 50085
9.7%
4 49933
9.6%
0 49825
9.6%

individualCount
Text

Distinct148
Distinct (%)0.1%
Missing124
Missing (%)0.1%
Memory size810.6 KiB
2025-01-23T18:14:56.515147image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.025817224
Min length1

Characters and Unicode

Total characters106288
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row10
3rd row1
4th row10
5th row1
ValueCountFrequency (%)
1 96000
92.7%
2 1407
 
1.4%
3 802
 
0.8%
4 721
 
0.7%
5 613
 
0.6%
6 510
 
0.5%
7 364
 
0.4%
8 326
 
0.3%
9 262
 
0.3%
10 249
 
0.2%
Other values (138) 2359
 
2.3%
2025-01-23T18:14:56.676979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 97843
92.1%
2 2242
 
2.1%
3 1338
 
1.3%
4 1117
 
1.1%
5 986
 
0.9%
6 774
 
0.7%
7 597
 
0.6%
8 501
 
0.5%
9 447
 
0.4%
0 443
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106288
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 97843
92.1%
2 2242
 
2.1%
3 1338
 
1.3%
4 1117
 
1.1%
5 986
 
0.9%
6 774
 
0.7%
7 597
 
0.6%
8 501
 
0.5%
9 447
 
0.4%
0 443
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 106288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 97843
92.1%
2 2242
 
2.1%
3 1338
 
1.3%
4 1117
 
1.1%
5 986
 
0.9%
6 774
 
0.7%
7 597
 
0.6%
8 501
 
0.5%
9 447
 
0.4%
0 443
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 97843
92.1%
2 2242
 
2.1%
3 1338
 
1.3%
4 1117
 
1.1%
5 986
 
0.9%
6 774
 
0.7%
7 597
 
0.6%
8 501
 
0.5%
9 447
 
0.4%
0 443
 
0.4%

sex
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing74008
Missing (%)71.3%
Memory size810.6 KiB
2025-01-23T18:14:56.722709image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.864812136
Min length4

Characters and Unicode

Total characters144626
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfemale
2nd rowfemale
3rd rowfemale
4th rowfemale
5th rowfemale
ValueCountFrequency (%)
male 16874
56.8%
female 12855
43.2%
2025-01-23T18:14:56.832741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 42584
29.4%
m 29729
20.6%
a 29729
20.6%
l 29729
20.6%
f 12855
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 144626
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42584
29.4%
m 29729
20.6%
a 29729
20.6%
l 29729
20.6%
f 12855
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 144626
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42584
29.4%
m 29729
20.6%
a 29729
20.6%
l 29729
20.6%
f 12855
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 42584
29.4%
m 29729
20.6%
a 29729
20.6%
l 29729
20.6%
f 12855
 
8.9%

lifeStage
Text

Missing 

Distinct15
Distinct (%)< 0.1%
Missing73653
Missing (%)71.0%
Memory size810.6 KiB
2025-01-23T18:14:56.885879image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.935680096
Min length6

Characters and Unicode

Total characters268821
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAdult(s)
2nd rowLarva(e)
3rd rowMetamorph(s)
4th rowAdult(s)
5th rowAdult(s)
ValueCountFrequency (%)
adult(s 12008
39.9%
juvenile(s 8637
28.7%
larva(e 7468
24.8%
subadult(s 573
 
1.9%
multiple 398
 
1.3%
metamorph(s 380
 
1.3%
egg(s 296
 
1.0%
eft(s 257
 
0.9%
embryo(s 57
 
0.2%
paedomorph(s 9
 
< 0.1%
2025-01-23T18:14:57.001789image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 29687
11.0%
) 29687
11.0%
e 25529
9.5%
s 22220
 
8.3%
u 22190
 
8.3%
l 22018
 
8.2%
v 16105
 
6.0%
a 15919
 
5.9%
t 13617
 
5.1%
d 12591
 
4.7%
Other values (18) 59258
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 179422
66.7%
Uppercase Letter 30025
 
11.2%
Open Punctuation 29687
 
11.0%
Close Punctuation 29687
 
11.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 25529
14.2%
s 22220
12.4%
u 22190
12.4%
l 22018
12.3%
v 16105
9.0%
a 15919
8.9%
t 13617
7.6%
d 12591
7.0%
i 9035
 
5.0%
n 8637
 
4.8%
Other values (9) 11561
6.4%
Uppercase Letter
ValueCountFrequency (%)
A 11988
39.9%
J 8637
28.8%
L 7465
24.9%
M 744
 
2.5%
E 610
 
2.0%
S 572
 
1.9%
P 9
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 29687
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 209447
77.9%
Common 59374
 
22.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 25529
12.2%
s 22220
10.6%
u 22190
10.6%
l 22018
10.5%
v 16105
7.7%
a 15919
7.6%
t 13617
 
6.5%
d 12591
 
6.0%
A 11988
 
5.7%
i 9035
 
4.3%
Other values (16) 38235
18.3%
Common
ValueCountFrequency (%)
( 29687
50.0%
) 29687
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 268821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 29687
11.0%
) 29687
11.0%
e 25529
9.5%
s 22220
 
8.3%
u 22190
 
8.3%
l 22018
 
8.2%
v 16105
 
6.0%
a 15919
 
5.9%
t 13617
 
5.1%
d 12591
 
4.7%
Other values (18) 59258
22.0%

disposition
Text

Distinct8
Distinct (%)< 0.1%
Missing423
Missing (%)0.4%
Memory size810.6 KiB
2025-01-23T18:14:57.056957image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.97125269
Min length4

Characters and Unicode

Total characters1443426
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowIn Collections
2nd rowIn Collections
3rd rowIn Collections
4th rowIn Collections
5th rowIn Collections
ValueCountFrequency (%)
in 102857
49.8%
collections 102857
49.8%
on 395
 
0.2%
loan 395
 
0.2%
deaccessioned 38
 
< 0.1%
exchanged 12
 
< 0.1%
lost 9
 
< 0.1%
released 1
 
< 0.1%
discarded 1
 
< 0.1%
exhibits 1
 
< 0.1%
2025-01-23T18:14:57.167460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 206554
14.3%
o 206156
14.3%
l 205715
14.3%
103252
7.2%
e 102987
7.1%
c 102946
7.1%
s 102945
7.1%
i 102898
7.1%
t 102867
7.1%
I 102857
7.1%
Other values (13) 104249
7.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1133608
78.5%
Uppercase Letter 206566
 
14.3%
Space Separator 103252
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 206554
18.2%
o 206156
18.2%
l 205715
18.1%
e 102987
9.1%
c 102946
9.1%
s 102945
9.1%
i 102898
9.1%
t 102867
9.1%
a 447
 
< 0.1%
d 53
 
< 0.1%
Other values (5) 40
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
I 102857
49.8%
C 102857
49.8%
L 404
 
0.2%
O 395
 
0.2%
D 39
 
< 0.1%
E 13
 
< 0.1%
R 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
103252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1340174
92.8%
Common 103252
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 206554
15.4%
o 206156
15.4%
l 205715
15.3%
e 102987
7.7%
c 102946
7.7%
s 102945
7.7%
i 102898
7.7%
t 102867
7.7%
I 102857
7.7%
C 102857
7.7%
Other values (12) 1392
 
0.1%
Common
ValueCountFrequency (%)
103252
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1443426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 206554
14.3%
o 206156
14.3%
l 205715
14.3%
103252
7.2%
e 102987
7.1%
c 102946
7.1%
s 102945
7.1%
i 102898
7.1%
t 102867
7.1%
I 102857
7.1%
Other values (13) 104249
7.2%

otherCatalogNumbers
Text

Missing 

Distinct51167
Distinct (%)85.9%
Missing44162
Missing (%)42.6%
Memory size810.6 KiB
2025-01-23T18:14:57.346965image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length67
Median length50
Mean length10.47041544
Min length1

Characters and Unicode

Total characters623775
Distinct characters78
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49321 ?
Unique (%)82.8%

Sample

1st rowRGA 99-37
2nd rowASU 10660
3rd rowJHH 65
4th rowDU A 14025
5th rowJCB 06-2373
ValueCountFrequency (%)
du 16715
 
11.2%
a 14454
 
9.7%
asu 11072
 
7.4%
chm 6225
 
4.2%
notes 4530
 
3.0%
vcu 3206
 
2.1%
r 3002
 
2.0%
eeb 2705
 
1.8%
wmp 2501
 
1.7%
field 1674
 
1.1%
Other values (29482) 83214
55.7%
2025-01-23T18:14:57.621373image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89803
 
14.4%
1 46092
 
7.4%
U 34523
 
5.5%
2 30396
 
4.9%
A 29625
 
4.7%
4 28015
 
4.5%
5 27473
 
4.4%
3 26607
 
4.3%
7 23898
 
3.8%
6 23599
 
3.8%
Other values (68) 263744
42.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 272014
43.6%
Uppercase Letter 182409
29.2%
Space Separator 89803
 
14.4%
Lowercase Letter 47334
 
7.6%
Other Punctuation 21067
 
3.4%
Dash Punctuation 5307
 
0.9%
Open Punctuation 2942
 
0.5%
Close Punctuation 2896
 
0.5%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 34523
18.9%
A 29625
16.2%
D 19738
10.8%
C 18672
10.2%
S 16194
8.9%
M 11442
 
6.3%
R 8402
 
4.6%
E 5767
 
3.2%
V 5593
 
3.1%
B 5294
 
2.9%
Other values (16) 27159
14.9%
Lowercase Letter
ValueCountFrequency (%)
e 8426
17.8%
h 6305
13.3%
o 5837
12.3%
t 4871
10.3%
s 4762
10.1%
l 3625
7.7%
n 3506
7.4%
r 1885
 
4.0%
i 1799
 
3.8%
d 1725
 
3.6%
Other values (15) 4593
9.7%
Decimal Number
ValueCountFrequency (%)
1 46092
16.9%
2 30396
11.2%
4 28015
10.3%
5 27473
10.1%
3 26607
9.8%
7 23898
8.8%
6 23599
8.7%
0 23510
8.6%
9 21628
8.0%
8 20796
7.6%
Other Punctuation
ValueCountFrequency (%)
. 12488
59.3%
; 6502
30.9%
, 1712
 
8.1%
# 233
 
1.1%
/ 105
 
0.5%
… 11
 
0.1%
" 6
 
< 0.1%
: 4
 
< 0.1%
' 3
 
< 0.1%
& 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2940
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2894
99.9%
] 2
 
0.1%
Space Separator
ValueCountFrequency (%)
89803
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5307
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 394032
63.2%
Latin 229743
36.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 34523
15.0%
A 29625
12.9%
D 19738
 
8.6%
C 18672
 
8.1%
S 16194
 
7.0%
M 11442
 
5.0%
e 8426
 
3.7%
R 8402
 
3.7%
h 6305
 
2.7%
o 5837
 
2.5%
Other values (41) 70579
30.7%
Common
ValueCountFrequency (%)
89803
22.8%
1 46092
11.7%
2 30396
 
7.7%
4 28015
 
7.1%
5 27473
 
7.0%
3 26607
 
6.8%
7 23898
 
6.1%
6 23599
 
6.0%
0 23510
 
6.0%
9 21628
 
5.5%
Other values (17) 53011
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 623764
> 99.9%
Punctuation 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89803
 
14.4%
1 46092
 
7.4%
U 34523
 
5.5%
2 30396
 
4.9%
A 29625
 
4.7%
4 28015
 
4.5%
5 27473
 
4.4%
3 26607
 
4.3%
7 23898
 
3.8%
6 23599
 
3.8%
Other values (67) 263733
42.3%
Punctuation
ValueCountFrequency (%)
… 11
100.0%

occurrenceRemarks
Text

Missing 

Distinct17288
Distinct (%)34.6%
Missing53843
Missing (%)51.9%
Memory size810.6 KiB
2025-01-23T18:14:57.815438image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length67057
Median length246
Mean length47.00803704
Min length1

Characters and Unicode

Total characters2345419
Distinct characters106
Distinct categories16 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13244 ?
Unique (%)26.5%

Sample

1st rowFrom isopropyl to formalin 6/26/01. (Adult Rana virgatipes from collection = NCSM 62072)
2nd rowAOR; died in captivity 27 August 1985
3rd rowPartial skeleton.
4th rowFound alive
5th rowMetamorph; eggs laid late February or March 1984; preserved 4 June 1984; metamorphs from tanks at Duke University; Tank 09; See H. M. Wilbur notes in species file and 1987 Ecology 68 (5): 1437-1452
ValueCountFrequency (%)
of 16289
 
4.2%
in 10340
 
2.7%
preserved 7938
 
2.0%
one 7667
 
2.0%
ncsm 7511
 
1.9%
a 6631
 
1.7%
dor 6364
 
1.6%
from 6156
 
1.6%
specimens 6127
 
1.6%
and 5823
 
1.5%
Other values (14148) 308249
79.2%
2025-01-23T18:14:58.097945image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
337280
 
14.4%
e 213872
 
9.1%
o 113442
 
4.8%
a 107967
 
4.6%
r 106567
 
4.5%
n 102775
 
4.4%
i 96025
 
4.1%
t 92178
 
3.9%
s 90635
 
3.9%
l 78351
 
3.3%
Other values (96) 1006327
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1461027
62.3%
Space Separator 337282
 
14.4%
Decimal Number 218924
 
9.3%
Uppercase Letter 188154
 
8.0%
Other Punctuation 74802
 
3.2%
Control 28247
 
1.2%
Open Punctuation 11515
 
0.5%
Close Punctuation 11321
 
0.5%
Dash Punctuation 10888
 
0.5%
Math Symbol 3148
 
0.1%
Other values (6) 111
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 213872
14.6%
o 113442
 
7.8%
a 107967
 
7.4%
r 106567
 
7.3%
n 102775
 
7.0%
i 96025
 
6.6%
t 92178
 
6.3%
s 90635
 
6.2%
l 78351
 
5.4%
d 67058
 
4.6%
Other values (20) 392157
26.8%
Uppercase Letter
ValueCountFrequency (%)
S 23079
12.3%
O 20545
10.9%
M 18260
9.7%
C 15056
 
8.0%
R 13840
 
7.4%
A 13221
 
7.0%
N 12107
 
6.4%
D 11903
 
6.3%
P 9939
 
5.3%
F 7972
 
4.2%
Other values (17) 42232
22.4%
Other Punctuation
ValueCountFrequency (%)
. 30037
40.2%
; 19030
25.4%
, 13419
17.9%
: 4190
 
5.6%
' 1896
 
2.5%
/ 1869
 
2.5%
" 1677
 
2.2%
* 1038
 
1.4%
# 498
 
0.7%
& 493
 
0.7%
Other values (5) 655
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 45045
20.6%
9 27997
12.8%
2 25361
11.6%
0 21685
9.9%
8 17653
 
8.1%
7 17573
 
8.0%
6 16374
 
7.5%
5 15933
 
7.3%
4 15917
 
7.3%
3 15386
 
7.0%
Math Symbol
ValueCountFrequency (%)
= 3088
98.1%
+ 56
 
1.8%
< 2
 
0.1%
~ 1
 
< 0.1%
> 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6619
57.5%
[ 4892
42.5%
{ 4
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6559
57.9%
] 4757
42.0%
} 5
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
° 74
88.1%
♀ 7
 
8.3%
♂ 3
 
3.6%
Space Separator
ValueCountFrequency (%)
337280
> 99.9%
  2
 
< 0.1%
Control
ValueCountFrequency (%)
28099
99.5%
148
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 10888
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 20
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3
100.0%
Other Letter
ValueCountFrequency (%)
º 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1649183
70.3%
Common 696236
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 213872
 
13.0%
o 113442
 
6.9%
a 107967
 
6.5%
r 106567
 
6.5%
n 102775
 
6.2%
i 96025
 
5.8%
t 92178
 
5.6%
s 90635
 
5.5%
l 78351
 
4.8%
d 67058
 
4.1%
Other values (48) 580313
35.2%
Common
ValueCountFrequency (%)
337280
48.4%
1 45045
 
6.5%
. 30037
 
4.3%
28099
 
4.0%
9 27997
 
4.0%
2 25361
 
3.6%
0 21685
 
3.1%
; 19030
 
2.7%
8 17653
 
2.5%
7 17573
 
2.5%
Other values (38) 126476
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2344632
> 99.9%
None 758
 
< 0.1%
Punctuation 19
 
< 0.1%
Misc Symbols 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
337280
 
14.4%
e 213872
 
9.1%
o 113442
 
4.8%
a 107967
 
4.6%
r 106567
 
4.5%
n 102775
 
4.4%
i 96025
 
4.1%
t 92178
 
3.9%
s 90635
 
3.9%
l 78351
 
3.3%
Other values (83) 1005540
42.9%
None
ValueCountFrequency (%)
ì 663
87.5%
° 74
 
9.8%
ú 9
 
1.2%
Ì 5
 
0.7%
º 2
 
0.3%
  2
 
0.3%
é 2
 
0.3%
í 1
 
0.1%
Punctuation
ValueCountFrequency (%)
… 17
89.5%
“ 1
 
5.3%
” 1
 
5.3%
Misc Symbols
ValueCountFrequency (%)
♀ 7
70.0%
♂ 3
30.0%

organismID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:14:58.202838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length251
Median length198
Mean length198
Min length145

Characters and Unicode

Total characters396
Distinct characters55
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowNCSM Ledger: NC: Alleghany Co., Tributary to Little River opposite Sandy Point, "Baileywick" (= J.R. Bailey property), ca. 6.25 airmi. ENE Sparta
2nd rowNCSM Ledger: NC: McDowell Co: vicinity of Marion Fish Hatchery, off CR 1436, ca. 6.0 mi. NW Marion; Personal Communication with Andrew at Buck Creek Trout Farm: several small hatcheries were located along Little Buck Creek Road beginning in the 1930s.
ValueCountFrequency (%)
ncsm 2
 
3.2%
ca 2
 
3.2%
nc 2
 
3.2%
co 2
 
3.2%
ledger 2
 
3.2%
little 2
 
3.2%
marion 2
 
3.2%
buck 2
 
3.2%
creek 2
 
3.2%
mi 1
 
1.6%
Other values (44) 44
69.8%
2025-01-23T18:14:58.360942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
15.4%
e 29
 
7.3%
i 25
 
6.3%
a 23
 
5.8%
r 21
 
5.3%
t 19
 
4.8%
o 19
 
4.8%
n 15
 
3.8%
l 14
 
3.5%
c 11
 
2.8%
Other values (45) 159
40.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 244
61.6%
Space Separator 61
 
15.4%
Uppercase Letter 51
 
12.9%
Other Punctuation 24
 
6.1%
Decimal Number 13
 
3.3%
Close Punctuation 1
 
0.3%
Math Symbol 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 29
11.9%
i 25
10.2%
a 23
 
9.4%
r 21
 
8.6%
t 19
 
7.8%
o 19
 
7.8%
n 15
 
6.1%
l 14
 
5.7%
c 11
 
4.5%
y 8
 
3.3%
Other values (12) 60
24.6%
Uppercase Letter
ValueCountFrequency (%)
C 10
19.6%
N 6
11.8%
M 5
9.8%
R 4
 
7.8%
B 4
 
7.8%
L 4
 
7.8%
S 4
 
7.8%
F 2
 
3.9%
E 2
 
3.9%
A 2
 
3.9%
Other values (6) 8
15.7%
Decimal Number
ValueCountFrequency (%)
6 3
23.1%
0 2
15.4%
3 2
15.4%
1 2
15.4%
2 1
 
7.7%
5 1
 
7.7%
4 1
 
7.7%
9 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 10
41.7%
: 6
25.0%
, 5
20.8%
" 2
 
8.3%
; 1
 
4.2%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 295
74.5%
Common 101
 
25.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 29
 
9.8%
i 25
 
8.5%
a 23
 
7.8%
r 21
 
7.1%
t 19
 
6.4%
o 19
 
6.4%
n 15
 
5.1%
l 14
 
4.7%
c 11
 
3.7%
C 10
 
3.4%
Other values (28) 109
36.9%
Common
ValueCountFrequency (%)
61
60.4%
. 10
 
9.9%
: 6
 
5.9%
, 5
 
5.0%
6 3
 
3.0%
0 2
 
2.0%
3 2
 
2.0%
1 2
 
2.0%
" 2
 
2.0%
) 1
 
1.0%
Other values (7) 7
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
 
15.4%
e 29
 
7.3%
i 25
 
6.3%
a 23
 
5.8%
r 21
 
5.3%
t 19
 
4.8%
o 19
 
4.8%
n 15
 
3.8%
l 14
 
3.5%
c 11
 
2.8%
Other values (45) 159
40.2%

parentEventID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:14:58.410403image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row34.1384
ValueCountFrequency (%)
34.1384 1
100.0%
2025-01-23T18:14:58.505923image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
28.6%
4 2
28.6%
. 1
14.3%
1 1
14.3%
8 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
85.7%
Other Punctuation 1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
33.3%
4 2
33.3%
1 1
16.7%
8 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
28.6%
4 2
28.6%
. 1
14.3%
1 1
14.3%
8 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
28.6%
4 2
28.6%
. 1
14.3%
1 1
14.3%
8 1
14.3%

eventType
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:14:58.551735image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.333333333
Min length7

Characters and Unicode

Total characters22
Distinct characters11
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row-78.3236
2nd row36.5431
3rd row35.7391
ValueCountFrequency (%)
78.3236 1
33.3%
36.5431 1
33.3%
35.7391 1
33.3%
2025-01-23T18:14:58.652923image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 6
27.3%
. 3
13.6%
7 2
 
9.1%
6 2
 
9.1%
5 2
 
9.1%
1 2
 
9.1%
- 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
4 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
81.8%
Other Punctuation 3
 
13.6%
Dash Punctuation 1
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 6
33.3%
7 2
 
11.1%
6 2
 
11.1%
5 2
 
11.1%
1 2
 
11.1%
8 1
 
5.6%
2 1
 
5.6%
4 1
 
5.6%
9 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 6
27.3%
. 3
13.6%
7 2
 
9.1%
6 2
 
9.1%
5 2
 
9.1%
1 2
 
9.1%
- 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
4 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 6
27.3%
. 3
13.6%
7 2
 
9.1%
6 2
 
9.1%
5 2
 
9.1%
1 2
 
9.1%
- 1
 
4.5%
8 1
 
4.5%
2 1
 
4.5%
4 1
 
4.5%

fieldNumber
Text

Distinct73049
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Memory size810.6 KiB
2025-01-23T18:14:58.857940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length49
Median length10
Mean length9.805961229
Min length1

Characters and Unicode

Total characters1017241
Distinct characters68
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64025 ?
Unique (%)61.7%

Sample

1st rowBLS 17192
2nd rowHERP-62585
3rd rowHERP-92192
4th rowALB 2235
5th rowHERP-25999
ValueCountFrequency (%)
alb 4933
 
3.8%
bls 3052
 
2.3%
jcb 2634
 
2.0%
jrh 1990
 
1.5%
wmp 1615
 
1.2%
eeb 825
 
0.6%
asfs 453
 
0.3%
hmw 394
 
0.3%
dsm 374
 
0.3%
rwg 373
 
0.3%
Other values (66744) 113349
87.2%
2025-01-23T18:14:59.147423image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 89088
 
8.8%
R 79032
 
7.8%
H 78530
 
7.7%
E 75932
 
7.5%
P 75781
 
7.4%
1 69394
 
6.8%
0 59671
 
5.9%
2 51860
 
5.1%
9 49478
 
4.9%
6 49156
 
4.8%
Other values (58) 339319
33.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 514255
50.6%
Uppercase Letter 382207
37.6%
Dash Punctuation 89088
 
8.8%
Space Separator 26262
 
2.6%
Lowercase Letter 4380
 
0.4%
Other Punctuation 759
 
0.1%
Connector Punctuation 136
 
< 0.1%
Close Punctuation 77
 
< 0.1%
Open Punctuation 77
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 79032
20.7%
H 78530
20.5%
E 75932
19.9%
P 75781
19.8%
B 14308
 
3.7%
L 9348
 
2.4%
J 8273
 
2.2%
S 7777
 
2.0%
A 7490
 
2.0%
M 5678
 
1.5%
Other values (16) 20058
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
a 746
17.0%
i 694
15.8%
b 549
12.5%
e 429
9.8%
n 365
8.3%
c 320
7.3%
d 172
 
3.9%
l 153
 
3.5%
r 146
 
3.3%
h 140
 
3.2%
Other values (12) 666
15.2%
Decimal Number
ValueCountFrequency (%)
1 69394
13.5%
0 59671
11.6%
2 51860
10.1%
9 49478
9.6%
6 49156
9.6%
5 49061
9.5%
3 48629
9.5%
4 47511
9.2%
7 44902
8.7%
8 44593
8.7%
Other Punctuation
ValueCountFrequency (%)
. 501
66.0%
; 143
 
18.8%
, 56
 
7.4%
/ 46
 
6.1%
# 13
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 89088
100.0%
Space Separator
ValueCountFrequency (%)
26262
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 630654
62.0%
Latin 386587
38.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 79032
20.4%
H 78530
20.3%
E 75932
19.6%
P 75781
19.6%
B 14308
 
3.7%
L 9348
 
2.4%
J 8273
 
2.1%
S 7777
 
2.0%
A 7490
 
1.9%
M 5678
 
1.5%
Other values (38) 24438
 
6.3%
Common
ValueCountFrequency (%)
- 89088
14.1%
1 69394
11.0%
0 59671
9.5%
2 51860
8.2%
9 49478
7.8%
6 49156
7.8%
5 49061
7.8%
3 48629
7.7%
4 47511
7.5%
7 44902
7.1%
Other values (10) 71904
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1017241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 89088
 
8.8%
R 79032
 
7.8%
H 78530
 
7.7%
E 75932
 
7.5%
P 75781
 
7.4%
1 69394
 
6.8%
0 59671
 
5.9%
2 51860
 
5.1%
9 49478
 
4.9%
6 49156
 
4.8%
Other values (58) 339319
33.4%

eventDate
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:14:59.201681image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS84
2nd rowWGS84
ValueCountFrequency (%)
wgs84 2
100.0%
2025-01-23T18:14:59.295476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
60.0%
Decimal Number 4
40.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 2
33.3%
G 2
33.3%
S 2
33.3%
Decimal Number
ValueCountFrequency (%)
8 2
50.0%
4 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
60.0%
Common 4
40.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 2
33.3%
G 2
33.3%
S 2
33.3%
Common
ValueCountFrequency (%)
8 2
50.0%
4 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W 2
20.0%
G 2
20.0%
S 2
20.0%
8 2
20.0%
4 2
20.0%

eventTime
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:14:59.336922image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row201
2nd row805
ValueCountFrequency (%)
201 1
50.0%
805 1
50.0%
2025-01-23T18:14:59.434458image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
1 1
16.7%
8 1
16.7%
5 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
1 1
16.7%
8 1
16.7%
5 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
1 1
16.7%
8 1
16.7%
5 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
1 1
16.7%
8 1
16.7%
5 1
16.7%

year
Text

Missing 

Distinct131
Distinct (%)0.1%
Missing4161
Missing (%)4.0%
Memory size810.6 KiB
2025-01-23T18:14:59.578429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters398304
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2015
2nd row1999
3rd row1984
4th row1977
5th row1977
ValueCountFrequency (%)
1980 3624
 
3.6%
1979 3305
 
3.3%
1967 3287
 
3.3%
1966 2756
 
2.8%
1965 2671
 
2.7%
1976 2668
 
2.7%
1963 2560
 
2.6%
1968 2407
 
2.4%
1974 2351
 
2.4%
1954 2231
 
2.2%
Other values (121) 71716
72.0%
2025-01-23T18:14:59.784613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 101335
25.4%
1 100241
25.2%
0 34157
 
8.6%
6 31814
 
8.0%
7 31118
 
7.8%
2 29870
 
7.5%
8 25382
 
6.4%
5 20207
 
5.1%
4 13108
 
3.3%
3 11072
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 398304
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 101335
25.4%
1 100241
25.2%
0 34157
 
8.6%
6 31814
 
8.0%
7 31118
 
7.8%
2 29870
 
7.5%
8 25382
 
6.4%
5 20207
 
5.1%
4 13108
 
3.3%
3 11072
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 398304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 101335
25.4%
1 100241
25.2%
0 34157
 
8.6%
6 31814
 
8.0%
7 31118
 
7.8%
2 29870
 
7.5%
8 25382
 
6.4%
5 20207
 
5.1%
4 13108
 
3.3%
3 11072
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 101335
25.4%
1 100241
25.2%
0 34157
 
8.6%
6 31814
 
8.0%
7 31118
 
7.8%
2 29870
 
7.5%
8 25382
 
6.4%
5 20207
 
5.1%
4 13108
 
3.3%
3 11072
 
2.8%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing6115
Missing (%)5.9%
Memory size810.6 KiB
2025-01-23T18:14:59.845800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters195244
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05
2nd row05
3rd row09
4th row08
5th row09
ValueCountFrequency (%)
07 13898
14.2%
05 13762
14.1%
04 12172
12.5%
06 11941
12.2%
03 9172
9.4%
08 8667
8.9%
09 8184
8.4%
10 7974
8.2%
02 3795
 
3.9%
11 3229
 
3.3%
Other values (2) 4828
 
4.9%
2025-01-23T18:14:59.951905image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91904
47.1%
1 19260
 
9.9%
7 13898
 
7.1%
5 13762
 
7.0%
4 12172
 
6.2%
6 11941
 
6.1%
3 9172
 
4.7%
8 8667
 
4.4%
9 8184
 
4.2%
2 6284
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195244
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91904
47.1%
1 19260
 
9.9%
7 13898
 
7.1%
5 13762
 
7.0%
4 12172
 
6.2%
6 11941
 
6.1%
3 9172
 
4.7%
8 8667
 
4.4%
9 8184
 
4.2%
2 6284
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 195244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91904
47.1%
1 19260
 
9.9%
7 13898
 
7.1%
5 13762
 
7.0%
4 12172
 
6.2%
6 11941
 
6.1%
3 9172
 
4.7%
8 8667
 
4.4%
9 8184
 
4.2%
2 6284
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 195244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91904
47.1%
1 19260
 
9.9%
7 13898
 
7.1%
5 13762
 
7.0%
4 12172
 
6.2%
6 11941
 
6.1%
3 9172
 
4.7%
8 8667
 
4.4%
9 8184
 
4.2%
2 6284
 
3.2%

day
Text

Missing 

Distinct42
Distinct (%)< 0.1%
Missing10618
Missing (%)10.2%
Memory size810.6 KiB
2025-01-23T18:15:00.034274image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.789677724
Min length1

Characters and Unicode

Total characters166653
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row15
2nd row08
3rd row22
4th row20
5th row17
ValueCountFrequency (%)
18 3389
 
3.6%
27 3327
 
3.6%
12 3269
 
3.5%
14 3257
 
3.5%
24 3243
 
3.5%
15 3211
 
3.4%
25 3189
 
3.4%
28 3154
 
3.4%
20 3146
 
3.4%
26 3121
 
3.4%
Other values (32) 60813
65.3%
2025-01-23T18:15:00.187386image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 41008
24.6%
2 40150
24.1%
0 16871
10.1%
3 13838
 
8.3%
4 9621
 
5.8%
5 9601
 
5.8%
8 9515
 
5.7%
6 9297
 
5.6%
7 8828
 
5.3%
9 7924
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 166653
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 41008
24.6%
2 40150
24.1%
0 16871
10.1%
3 13838
 
8.3%
4 9621
 
5.8%
5 9601
 
5.8%
8 9515
 
5.7%
6 9297
 
5.6%
7 8828
 
5.3%
9 7924
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 166653
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 41008
24.6%
2 40150
24.1%
0 16871
10.1%
3 13838
 
8.3%
4 9621
 
5.8%
5 9601
 
5.8%
8 9515
 
5.7%
6 9297
 
5.6%
7 8828
 
5.3%
9 7924
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 41008
24.6%
2 40150
24.1%
0 16871
10.1%
3 13838
 
8.3%
4 9621
 
5.8%
5 9601
 
5.8%
8 9515
 
5.7%
6 9297
 
5.6%
7 8828
 
5.3%
9 7924
 
4.8%

eventRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:00.245880image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPersonal Communication
ValueCountFrequency (%)
personal 1
50.0%
communication 1
50.0%
2025-01-23T18:15:00.350270image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3
13.6%
n 3
13.6%
a 2
 
9.1%
m 2
 
9.1%
i 2
 
9.1%
P 1
 
4.5%
e 1
 
4.5%
r 1
 
4.5%
s 1
 
4.5%
l 1
 
4.5%
Other values (5) 5
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19
86.4%
Uppercase Letter 2
 
9.1%
Space Separator 1
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3
15.8%
n 3
15.8%
a 2
10.5%
m 2
10.5%
i 2
10.5%
e 1
 
5.3%
r 1
 
5.3%
s 1
 
5.3%
l 1
 
5.3%
u 1
 
5.3%
Other values (2) 2
10.5%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
95.5%
Common 1
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3
14.3%
n 3
14.3%
a 2
9.5%
m 2
9.5%
i 2
9.5%
P 1
 
4.8%
e 1
 
4.8%
r 1
 
4.8%
s 1
 
4.8%
l 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3
13.6%
n 3
13.6%
a 2
 
9.1%
m 2
 
9.1%
i 2
 
9.1%
P 1
 
4.5%
e 1
 
4.5%
r 1
 
4.5%
s 1
 
4.5%
l 1
 
4.5%
Other values (5) 5
22.7%

locationID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:00.412376image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length42
Median length38.5
Mean length38.5
Min length35

Characters and Unicode

Total characters77
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDeLorme Topo USA 6.0, Alleghany County GIS
2nd rowPersonal Communication, Google Maps
ValueCountFrequency (%)
delorme 1
9.1%
topo 1
9.1%
usa 1
9.1%
6.0 1
9.1%
alleghany 1
9.1%
county 1
9.1%
gis 1
9.1%
personal 1
9.1%
communication 1
9.1%
google 1
9.1%
2025-01-23T18:15:00.542757image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 9
 
11.7%
9
 
11.7%
n 5
 
6.5%
e 5
 
6.5%
l 4
 
5.2%
a 4
 
5.2%
m 3
 
3.9%
G 2
 
2.6%
y 2
 
2.6%
t 2
 
2.6%
Other values (22) 32
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 48
62.3%
Uppercase Letter 15
 
19.5%
Space Separator 9
 
11.7%
Other Punctuation 3
 
3.9%
Decimal Number 2
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9
18.8%
n 5
10.4%
e 5
10.4%
l 4
 
8.3%
a 4
 
8.3%
m 3
 
6.2%
y 2
 
4.2%
t 2
 
4.2%
g 2
 
4.2%
u 2
 
4.2%
Other values (6) 10
20.8%
Uppercase Letter
ValueCountFrequency (%)
G 2
13.3%
A 2
13.3%
S 2
13.3%
C 2
13.3%
I 1
6.7%
P 1
6.7%
D 1
6.7%
U 1
6.7%
T 1
6.7%
L 1
6.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
81.8%
Common 14
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 9
 
14.3%
n 5
 
7.9%
e 5
 
7.9%
l 4
 
6.3%
a 4
 
6.3%
m 3
 
4.8%
G 2
 
3.2%
y 2
 
3.2%
t 2
 
3.2%
g 2
 
3.2%
Other values (17) 25
39.7%
Common
ValueCountFrequency (%)
9
64.3%
, 2
 
14.3%
0 1
 
7.1%
. 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 9
 
11.7%
9
 
11.7%
n 5
 
6.5%
e 5
 
6.5%
l 4
 
5.2%
a 4
 
5.2%
m 3
 
3.9%
G 2
 
2.6%
y 2
 
2.6%
t 2
 
2.6%
Other values (22) 32
41.6%

continent
Text

Distinct6
Distinct (%)< 0.1%
Missing171
Missing (%)0.2%
Memory size810.6 KiB
2025-01-23T18:15:00.594536image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.57928278
Min length4

Characters and Unicode

Total characters1302786
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAsia
2nd rowNorth America
3rd rowNorth America
4th rowNorth America
5th rowNorth America
ValueCountFrequency (%)
america 98574
48.8%
north 98499
48.7%
asia 4320
 
2.1%
africa 644
 
0.3%
south 75
 
< 0.1%
europe 24
 
< 0.1%
australia 4
 
< 0.1%
2025-01-23T18:15:00.698418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 197745
15.2%
a 103546
7.9%
i 103542
7.9%
A 103542
7.9%
c 99218
7.6%
e 98598
7.6%
o 98598
7.6%
t 98578
7.6%
h 98574
7.6%
98574
7.6%
Other values (9) 202271
15.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1002072
76.9%
Uppercase Letter 202140
 
15.5%
Space Separator 98574
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 197745
19.7%
a 103546
10.3%
i 103542
10.3%
c 99218
9.9%
e 98598
9.8%
o 98598
9.8%
t 98578
9.8%
h 98574
9.8%
m 98574
9.8%
s 4324
 
0.4%
Other values (4) 775
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 103542
51.2%
N 98499
48.7%
S 75
 
< 0.1%
E 24
 
< 0.1%
Space Separator
ValueCountFrequency (%)
98574
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1204212
92.4%
Common 98574
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 197745
16.4%
a 103546
8.6%
i 103542
8.6%
A 103542
8.6%
c 99218
8.2%
e 98598
8.2%
o 98598
8.2%
t 98578
8.2%
h 98574
8.2%
m 98574
8.2%
Other values (8) 103697
8.6%
Common
ValueCountFrequency (%)
98574
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1302786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 197745
15.2%
a 103546
7.9%
i 103542
7.9%
A 103542
7.9%
c 99218
7.6%
e 98598
7.6%
o 98598
7.6%
t 98578
7.6%
h 98574
7.6%
98574
7.6%
Other values (9) 202271
15.5%

country
Text

Distinct55
Distinct (%)0.1%
Missing131
Missing (%)0.1%
Memory size810.6 KiB
2025-01-23T18:15:00.774387image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length13
Mean length12.61125804
Min length4

Characters and Unicode

Total characters1306602
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowLaos
2nd rowUnited States
3rd rowUnited States
4th rowUnited States
5th rowUnited States
ValueCountFrequency (%)
united 97851
48.4%
states 97851
48.4%
laos 2780
 
1.4%
vietnam 443
 
0.2%
cambodia 402
 
0.2%
gabon 346
 
0.2%
malaysia 341
 
0.2%
cuba 304
 
0.2%
guinea 252
 
0.1%
equatorial 247
 
0.1%
Other values (57) 1169
 
0.6%
2025-01-23T18:15:00.917938image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 294461
22.5%
e 196872
15.1%
a 105345
 
8.1%
s 101147
 
7.7%
i 100251
 
7.7%
n 99426
 
7.6%
d 98421
 
7.5%
98380
 
7.5%
S 97863
 
7.5%
U 97861
 
7.5%
Other values (36) 16575
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1006253
77.0%
Uppercase Letter 201939
 
15.5%
Space Separator 98380
 
7.5%
Dash Punctuation 30
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 294461
29.3%
e 196872
19.6%
a 105345
 
10.5%
s 101147
 
10.1%
i 100251
 
10.0%
n 99426
 
9.9%
d 98421
 
9.8%
o 4274
 
0.4%
b 1140
 
0.1%
u 1133
 
0.1%
Other values (15) 3783
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
S 97863
48.5%
U 97861
48.5%
L 2811
 
1.4%
C 1073
 
0.5%
G 617
 
0.3%
M 447
 
0.2%
V 444
 
0.2%
E 258
 
0.1%
B 170
 
0.1%
R 146
 
0.1%
Other values (9) 249
 
0.1%
Space Separator
ValueCountFrequency (%)
98380
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1208192
92.5%
Common 98410
 
7.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 294461
24.4%
e 196872
16.3%
a 105345
 
8.7%
s 101147
 
8.4%
i 100251
 
8.3%
n 99426
 
8.2%
d 98421
 
8.1%
S 97863
 
8.1%
U 97861
 
8.1%
o 4274
 
0.4%
Other values (34) 12271
 
1.0%
Common
ValueCountFrequency (%)
98380
> 99.9%
- 30
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1306534
> 99.9%
None 68
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 294461
22.5%
e 196872
15.1%
a 105345
 
8.1%
s 101147
 
7.7%
i 100251
 
7.7%
n 99426
 
7.6%
d 98421
 
7.5%
98380
 
7.5%
S 97863
 
7.5%
U 97861
 
7.5%
Other values (35) 16507
 
1.3%
None
ValueCountFrequency (%)
ç 68
100.0%

stateProvince
Text

Distinct193
Distinct (%)0.2%
Missing372
Missing (%)0.4%
Memory size810.6 KiB
2025-01-23T18:15:01.074804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length26
Median length14
Mean length12.63301891
Min length4

Characters and Unicode

Total characters1305812
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)< 0.1%

Sample

1st rowPhongsali
2nd rowNew Jersey
3rd rowKentucky
4th rowNorth Carolina
5th rowNorth Carolina
ValueCountFrequency (%)
carolina 78368
42.2%
north 67219
36.2%
south 11204
 
6.0%
virginia 6893
 
3.7%
new 2206
 
1.2%
florida 1941
 
1.0%
georgia 1721
 
0.9%
york 1338
 
0.7%
tennessee 966
 
0.5%
texas 796
 
0.4%
Other values (233) 12899
 
7.0%
2025-01-23T18:15:01.295275image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 183553
14.1%
o 169946
13.0%
r 161527
12.4%
i 110029
8.4%
n 96215
7.4%
l 83558
6.4%
82186
6.3%
h 81638
6.3%
t 81150
6.2%
C 79456
6.1%
Other values (54) 176554
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1037299
79.4%
Uppercase Letter 185887
 
14.2%
Space Separator 82186
 
6.3%
Dash Punctuation 405
 
< 0.1%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 183553
17.7%
o 169946
16.4%
r 161527
15.6%
i 110029
10.6%
n 96215
9.3%
l 83558
8.1%
h 81638
7.9%
t 81150
7.8%
u 14963
 
1.4%
e 14288
 
1.4%
Other values (22) 40432
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
C 79456
42.7%
N 69678
37.5%
S 12442
 
6.7%
V 7030
 
3.8%
T 2080
 
1.1%
F 1950
 
1.0%
G 1923
 
1.0%
Y 1340
 
0.7%
M 1165
 
0.6%
K 1155
 
0.6%
Other values (16) 7668
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
' 3
42.9%
Space Separator
ValueCountFrequency (%)
82186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 405
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1223186
93.7%
Common 82626
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 183553
15.0%
o 169946
13.9%
r 161527
13.2%
i 110029
9.0%
n 96215
7.9%
l 83558
6.8%
h 81638
6.7%
t 81150
6.6%
C 79456
6.5%
N 69678
 
5.7%
Other values (48) 106436
8.7%
Common
ValueCountFrequency (%)
82186
99.5%
- 405
 
0.5%
( 14
 
< 0.1%
) 14
 
< 0.1%
. 4
 
< 0.1%
' 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1305441
> 99.9%
None 371
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 183553
14.1%
o 169946
13.0%
r 161527
12.4%
i 110029
8.4%
n 96215
7.4%
l 83558
6.4%
82186
6.3%
h 81638
6.3%
t 81150
6.2%
C 79456
6.1%
Other values (47) 176183
13.5%
None
ValueCountFrequency (%)
é 333
89.8%
í 15
 
4.0%
ü 8
 
2.2%
á 7
 
1.9%
ā 5
 
1.3%
ī 2
 
0.5%
ó 1
 
0.3%

county
Text

Missing 

Distinct1136
Distinct (%)1.2%
Missing6969
Missing (%)6.7%
Memory size810.6 KiB
2025-01-23T18:15:01.497202image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length25
Mean length7.210141782
Min length3

Characters and Unicode

Total characters697711
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique277 ?
Unique (%)0.3%

Sample

1st rowPhongsaly
2nd rowBurlington
3rd rowHarlan
4th rowMcDowell
5th rowJohnston
ValueCountFrequency (%)
watauga 5147
 
5.0%
wake 3746
 
3.7%
macon 3293
 
3.2%
sampson 2219
 
2.2%
scotland 2051
 
2.0%
brunswick 2040
 
2.0%
jackson 1984
 
1.9%
bladen 1946
 
1.9%
moore 1747
 
1.7%
new 1631
 
1.6%
Other values (1181) 76309
74.7%
2025-01-23T18:15:01.767785image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 76278
 
10.9%
e 71272
 
10.2%
n 58116
 
8.3%
o 50352
 
7.2%
r 45805
 
6.6%
l 34105
 
4.9%
t 29123
 
4.2%
s 26346
 
3.8%
u 24236
 
3.5%
i 23947
 
3.4%
Other values (57) 258131
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 587409
84.2%
Uppercase Letter 103686
 
14.9%
Space Separator 5346
 
0.8%
Dash Punctuation 986
 
0.1%
Other Punctuation 271
 
< 0.1%
Currency Symbol 11
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 76278
13.0%
e 71272
12.1%
n 58116
 
9.9%
o 50352
 
8.6%
r 45805
 
7.8%
l 34105
 
5.8%
t 29123
 
5.0%
s 26346
 
4.5%
u 24236
 
4.1%
i 23947
 
4.1%
Other values (21) 147829
25.2%
Uppercase Letter
ValueCountFrequency (%)
C 12274
11.8%
B 11249
10.8%
W 11189
10.8%
M 9649
 
9.3%
S 8191
 
7.9%
H 7269
 
7.0%
D 5780
 
5.6%
P 4770
 
4.6%
R 4309
 
4.2%
O 4287
 
4.1%
Other values (16) 24719
23.8%
Other Punctuation
ValueCountFrequency (%)
. 237
87.5%
' 17
 
6.3%
/ 15
 
5.5%
: 2
 
0.7%
Space Separator
ValueCountFrequency (%)
5345
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 986
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 11
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 691095
99.1%
Common 6616
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 76278
 
11.0%
e 71272
 
10.3%
n 58116
 
8.4%
o 50352
 
7.3%
r 45805
 
6.6%
l 34105
 
4.9%
t 29123
 
4.2%
s 26346
 
3.8%
u 24236
 
3.5%
i 23947
 
3.5%
Other values (47) 251515
36.4%
Common
ValueCountFrequency (%)
5345
80.8%
- 986
 
14.9%
. 237
 
3.6%
' 17
 
0.3%
/ 15
 
0.2%
¤ 11
 
0.2%
: 2
 
< 0.1%
[ 1
 
< 0.1%
] 1
 
< 0.1%
  1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 697675
> 99.9%
None 36
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 76278
 
10.9%
e 71272
 
10.2%
n 58116
 
8.3%
o 50352
 
7.2%
r 45805
 
6.6%
l 34105
 
4.9%
t 29123
 
4.2%
s 26346
 
3.8%
u 24236
 
3.5%
i 23947
 
3.4%
Other values (50) 258095
37.0%
None
ValueCountFrequency (%)
á 15
41.7%
¤ 11
30.6%
ñ 5
 
13.9%
ó 2
 
5.6%
í 1
 
2.8%
ô 1
 
2.8%
  1
 
2.8%

municipality
Text

Missing 

Distinct109
Distinct (%)12.3%
Missing102849
Missing (%)99.1%
Memory size810.6 KiB
2025-01-23T18:15:01.903809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.00900901
Min length4

Characters and Unicode

Total characters8888
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)4.2%

Sample

1st rowROWAN
2nd rowRED SPRINGS
3rd rowMAPLE HILL
4th rowWILMINGTON
5th rowWILMINGTON
ValueCountFrequency (%)
beach 145
 
12.0%
wilmington 144
 
11.9%
carolina 129
 
10.7%
laurinburg 55
 
4.5%
hill 35
 
2.9%
wakulla 30
 
2.5%
lake 29
 
2.4%
ingold 26
 
2.1%
silver 25
 
2.1%
rowan 23
 
1.9%
Other values (102) 569
47.0%
2025-01-23T18:15:02.243382image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 900
 
10.1%
L 769
 
8.7%
N 726
 
8.2%
I 670
 
7.5%
O 620
 
7.0%
R 564
 
6.3%
E 479
 
5.4%
T 396
 
4.5%
B 347
 
3.9%
C 341
 
3.8%
Other values (39) 3076
34.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8001
90.0%
Lowercase Letter 565
 
6.4%
Space Separator 322
 
3.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 900
11.2%
L 769
 
9.6%
N 726
 
9.1%
I 670
 
8.4%
O 620
 
7.7%
R 564
 
7.0%
E 479
 
6.0%
T 396
 
4.9%
B 347
 
4.3%
C 341
 
4.3%
Other values (15) 2189
27.4%
Lowercase Letter
ValueCountFrequency (%)
n 60
10.6%
o 58
10.3%
a 55
9.7%
i 54
9.6%
e 48
 
8.5%
t 43
 
7.6%
l 42
 
7.4%
m 32
 
5.7%
r 29
 
5.1%
c 23
 
4.1%
Other values (13) 121
21.4%
Space Separator
ValueCountFrequency (%)
322
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8566
96.4%
Common 322
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 900
 
10.5%
L 769
 
9.0%
N 726
 
8.5%
I 670
 
7.8%
O 620
 
7.2%
R 564
 
6.6%
E 479
 
5.6%
T 396
 
4.6%
B 347
 
4.1%
C 341
 
4.0%
Other values (38) 2754
32.2%
Common
ValueCountFrequency (%)
322
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 900
 
10.1%
L 769
 
8.7%
N 726
 
8.2%
I 670
 
7.5%
O 620
 
7.0%
R 564
 
6.3%
E 479
 
5.4%
T 396
 
4.5%
B 347
 
3.9%
C 341
 
3.8%
Other values (39) 3076
34.6%

locality
Text

Missing 

Distinct36290
Distinct (%)37.1%
Missing6009
Missing (%)5.8%
Memory size810.6 KiB
2025-01-23T18:15:02.437009image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24661
Median length178
Mean length66.5424648
Min length1

Characters and Unicode

Total characters6503062
Distinct characters102
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24175 ?
Unique (%)24.7%

Sample

1st rowPhou Dendin National Protected Area, Houay Lick
2nd rowca. 2-3 miles S Chatsworth
3rd rowU.S. 119, 1.9 rdmi. S. Hiram, [ca. 1.9 airmi. WSW center Hiram].
4th rowAlong tributary to Swannanoa Creek, along SR 1400 [Old U.S. 70 W], 1.3 rdmi. W jct. SR 1407 [Mill Creek Rd.], [ca. 3.2 airmi. WNW center] Old Fort (town)
5th rowca. 1.4 mi. SSW Clayton
ValueCountFrequency (%)
ca 66173
 
6.0%
center 54068
 
4.9%
airmi 51321
 
4.6%
rd 27911
 
2.5%
sr 25553
 
2.3%
miles 18501
 
1.7%
jct 14144
 
1.3%
creek 13005
 
1.2%
rdmi 12223
 
1.1%
s 10150
 
0.9%
Other values (15716) 816984
73.6%
2025-01-23T18:15:02.711854image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1012567
 
15.6%
e 424425
 
6.5%
a 400201
 
6.2%
i 342173
 
5.3%
r 327411
 
5.0%
. 325858
 
5.0%
n 275560
 
4.2%
o 230133
 
3.5%
t 225085
 
3.5%
l 197592
 
3.0%
Other values (92) 2742057
42.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3514030
54.0%
Space Separator 1012620
 
15.6%
Uppercase Letter 799649
 
12.3%
Other Punctuation 462628
 
7.1%
Decimal Number 424465
 
6.5%
Open Punctuation 138243
 
2.1%
Close Punctuation 138016
 
2.1%
Control 5851
 
0.1%
Dash Punctuation 5562
 
0.1%
Math Symbol 1876
 
< 0.1%
Other values (4) 122
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 424425
12.1%
a 400201
11.4%
i 342173
9.7%
r 327411
9.3%
n 275560
 
7.8%
o 230133
 
6.5%
t 225085
 
6.4%
l 197592
 
5.6%
c 184212
 
5.2%
m 151286
 
4.3%
Other values (23) 755952
21.5%
Uppercase Letter
ValueCountFrequency (%)
S 140368
17.6%
N 89557
11.2%
R 86858
10.9%
W 75570
9.5%
C 69616
8.7%
E 64733
8.1%
B 34392
 
4.3%
H 30830
 
3.9%
M 30644
 
3.8%
P 23702
 
3.0%
Other values (16) 153379
19.2%
Other Punctuation
ValueCountFrequency (%)
. 325858
70.4%
, 121957
 
26.4%
/ 6236
 
1.3%
" 3901
 
0.8%
' 2472
 
0.5%
? 843
 
0.2%
; 484
 
0.1%
: 455
 
0.1%
# 325
 
0.1%
& 86
 
< 0.1%
Other values (3) 11
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 88534
20.9%
5 58167
13.7%
0 56892
13.4%
2 50628
11.9%
3 38106
9.0%
4 37669
8.9%
6 27887
 
6.6%
7 27753
 
6.5%
8 20306
 
4.8%
9 18523
 
4.4%
Math Symbol
ValueCountFrequency (%)
= 1468
78.3%
< 377
 
20.1%
> 20
 
1.1%
+ 10
 
0.5%
~ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
[ 124915
90.4%
( 13322
 
9.6%
{ 6
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
] 124739
90.4%
) 13272
 
9.6%
} 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1012567
> 99.9%
  53
 
< 0.1%
Control
ValueCountFrequency (%)
5820
99.5%
31
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 5562
100.0%
Other Symbol
ValueCountFrequency (%)
° 104
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4313679
66.3%
Common 2189383
33.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 424425
 
9.8%
a 400201
 
9.3%
i 342173
 
7.9%
r 327411
 
7.6%
n 275560
 
6.4%
o 230133
 
5.3%
t 225085
 
5.2%
l 197592
 
4.6%
c 184212
 
4.3%
m 151286
 
3.5%
Other values (49) 1555601
36.1%
Common
ValueCountFrequency (%)
1012567
46.2%
. 325858
 
14.9%
[ 124915
 
5.7%
] 124739
 
5.7%
, 121957
 
5.6%
1 88534
 
4.0%
5 58167
 
2.7%
0 56892
 
2.6%
2 50628
 
2.3%
3 38106
 
1.7%
Other values (33) 187020
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6502689
> 99.9%
None 361
 
< 0.1%
Punctuation 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1012567
 
15.6%
e 424425
 
6.5%
a 400201
 
6.2%
i 342173
 
5.3%
r 327411
 
5.0%
. 325858
 
5.0%
n 275560
 
4.2%
o 230133
 
3.5%
t 225085
 
3.5%
l 197592
 
3.0%
Other values (81) 2741684
42.2%
None
ValueCountFrequency (%)
é 186
51.5%
° 104
28.8%
  53
 
14.7%
ñ 9
 
2.5%
í 3
 
0.8%
ç 2
 
0.6%
ó 2
 
0.6%
á 1
 
0.3%
ã 1
 
0.3%
Punctuation
ValueCountFrequency (%)
’ 11
91.7%
“ 1
 
8.3%

verbatimLocality
Text

Missing 

Distinct23378
Distinct (%)44.5%
Missing51237
Missing (%)49.4%
Memory size810.6 KiB
2025-01-23T18:15:02.910244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length255
Median length201
Mean length108.8073333
Min length1

Characters and Unicode

Total characters5712385
Distinct characters104
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16652 ?
Unique (%)31.7%

Sample

1st rowNCSM Ledger: NC: McDowell Co: under rocks & debris along trib. of Swannanoa Cr. along CR 1400, 1.3 rd.mi. W jct. CR 1407, 3.0 mi. W.NW Old Fort (town)
2nd rowNCSM Ledger: NC: Scotland Co: Sandhills Gamelands
3rd rowNCSM Ledger: NC: New Hanover Co: drift fence trap off SSR 1573, .3 rdmi. N. jct. SSR 1539, Trap No. 2, 1 1/4 mi. SW Carolina Beach (town)
4th rowNCSM Ledger: Canada: New Brunswick: University Forest, University of New Brunswick; Duke University card: same
5th rowASU Catalog: SC: Charleston Co: Francis Marion National Forest, N 33.144795, W -79.695625
ValueCountFrequency (%)
co 54514
 
5.4%
ncsm 39607
 
3.9%
ledger 39190
 
3.9%
nc 36012
 
3.6%
mi 35250
 
3.5%
of 10409
 
1.0%
ca 9044
 
0.9%
n 8807
 
0.9%
rd 8460
 
0.8%
data 8366
 
0.8%
Other values (18194) 762215
75.3%
2025-01-23T18:15:03.184834image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
963366
 
16.9%
e 380345
 
6.7%
a 300460
 
5.3%
o 278652
 
4.9%
r 246808
 
4.3%
n 219299
 
3.8%
i 214621
 
3.8%
C 206316
 
3.6%
t 188131
 
3.3%
. 165934
 
2.9%
Other values (94) 2548453
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3025754
53.0%
Space Separator 963379
 
16.9%
Uppercase Letter 892884
 
15.6%
Other Punctuation 459681
 
8.0%
Decimal Number 331666
 
5.8%
Open Punctuation 11556
 
0.2%
Close Punctuation 11483
 
0.2%
Dash Punctuation 10109
 
0.2%
Other Symbol 2879
 
0.1%
Math Symbol 2810
 
< 0.1%
Other values (4) 184
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 380345
12.6%
a 300460
 
9.9%
o 278652
 
9.2%
r 246808
 
8.2%
n 219299
 
7.2%
i 214621
 
7.1%
t 188131
 
6.2%
d 156715
 
5.2%
l 155594
 
5.1%
s 133374
 
4.4%
Other values (22) 751755
24.8%
Uppercase Letter
ValueCountFrequency (%)
C 206316
23.1%
S 127754
14.3%
N 110458
12.4%
M 71903
 
8.1%
L 54016
 
6.0%
R 53309
 
6.0%
W 37106
 
4.2%
D 26814
 
3.0%
A 25922
 
2.9%
B 25569
 
2.9%
Other values (16) 153717
17.2%
Other Punctuation
ValueCountFrequency (%)
. 165934
36.1%
: 164279
35.7%
, 96513
21.0%
; 16025
 
3.5%
' 5576
 
1.2%
" 4945
 
1.1%
/ 4636
 
1.0%
& 887
 
0.2%
# 533
 
0.1%
? 283
 
0.1%
Other values (3) 70
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 66493
20.0%
0 46249
13.9%
2 42028
12.7%
3 35036
10.6%
5 34783
10.5%
4 29071
8.8%
7 21684
 
6.5%
6 20874
 
6.3%
8 17858
 
5.4%
9 17590
 
5.3%
Math Symbol
ValueCountFrequency (%)
= 2372
84.4%
+ 185
 
6.6%
< 148
 
5.3%
~ 103
 
3.7%
> 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 7875
68.1%
[ 3678
31.8%
{ 3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 7834
68.2%
] 3646
31.8%
} 3
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
° 2853
99.1%
♀ 18
 
0.6%
♂ 8
 
0.3%
Space Separator
ValueCountFrequency (%)
963366
> 99.9%
  13
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 10105
> 99.9%
– 4
 
< 0.1%
Other Number
ValueCountFrequency (%)
² 1
50.0%
¼ 1
50.0%
Other Letter
ValueCountFrequency (%)
º 132
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 47
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3918770
68.6%
Common 1793615
31.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 380345
 
9.7%
a 300460
 
7.7%
o 278652
 
7.1%
r 246808
 
6.3%
n 219299
 
5.6%
i 214621
 
5.5%
C 206316
 
5.3%
t 188131
 
4.8%
d 156715
 
4.0%
l 155594
 
4.0%
Other values (49) 1571829
40.1%
Common
ValueCountFrequency (%)
963366
53.7%
. 165934
 
9.3%
: 164279
 
9.2%
, 96513
 
5.4%
1 66493
 
3.7%
0 46249
 
2.6%
2 42028
 
2.3%
3 35036
 
2.0%
5 34783
 
1.9%
4 29071
 
1.6%
Other values (35) 149863
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5709317
99.9%
None 3019
 
0.1%
Misc Symbols 26
 
< 0.1%
Punctuation 23
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
963366
 
16.9%
e 380345
 
6.7%
a 300460
 
5.3%
o 278652
 
4.9%
r 246808
 
4.3%
n 219299
 
3.8%
i 214621
 
3.8%
C 206316
 
3.6%
t 188131
 
3.3%
. 165934
 
2.9%
Other values (78) 2545385
44.6%
None
ValueCountFrequency (%)
° 2853
94.5%
º 132
 
4.4%
  13
 
0.4%
ú 10
 
0.3%
ó 4
 
0.1%
é 2
 
0.1%
² 1
 
< 0.1%
¼ 1
 
< 0.1%
ñ 1
 
< 0.1%
í 1
 
< 0.1%
Misc Symbols
ValueCountFrequency (%)
♀ 18
69.2%
♂ 8
30.8%
Punctuation
ValueCountFrequency (%)
… 16
69.6%
– 4
 
17.4%
’ 3
 
13.0%

locationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:03.240365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters21
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row34.8546
2nd row34.8546
3rd row34.8546
ValueCountFrequency (%)
34.8546 3
100.0%
2025-01-23T18:15:03.335897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 6
28.6%
3 3
14.3%
. 3
14.3%
8 3
14.3%
5 3
14.3%
6 3
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
85.7%
Other Punctuation 3
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6
33.3%
3 3
16.7%
8 3
16.7%
5 3
16.7%
6 3
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 6
28.6%
3 3
14.3%
. 3
14.3%
8 3
14.3%
5 3
14.3%
6 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 6
28.6%
3 3
14.3%
. 3
14.3%
8 3
14.3%
5 3
14.3%
6 3
14.3%

decimalLatitude
Text

Missing 

Distinct23698
Distinct (%)24.4%
Missing6514
Missing (%)6.3%
Memory size810.6 KiB
2025-01-23T18:15:03.542353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.873075301
Min length3

Characters and Unicode

Total characters668221
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10794 ?
Unique (%)11.1%

Sample

1st row22.0652
2nd row39.7812
3rd row36.9516
4th row35.638
5th row35.633
ValueCountFrequency (%)
36.2224 1539
 
1.6%
36.1142 762
 
0.8%
35.7801 600
 
0.6%
36.241 279
 
0.3%
35.0526 260
 
0.3%
36.2264 257
 
0.3%
35.9242 230
 
0.2%
34.8494 223
 
0.2%
36.0039 214
 
0.2%
37.3759 208
 
0.2%
Other values (23682) 92651
95.3%
2025-01-23T18:15:03.812370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 127903
19.1%
. 97223
14.5%
5 73918
11.1%
4 63625
9.5%
6 53034
7.9%
2 51820
7.8%
1 45628
 
6.8%
9 41949
 
6.3%
7 40707
 
6.1%
8 36804
 
5.5%
Other values (2) 35610
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570701
85.4%
Other Punctuation 97223
 
14.5%
Dash Punctuation 297
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 127903
22.4%
5 73918
13.0%
4 63625
11.1%
6 53034
9.3%
2 51820
9.1%
1 45628
 
8.0%
9 41949
 
7.4%
7 40707
 
7.1%
8 36804
 
6.4%
0 35313
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 97223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 668221
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 127903
19.1%
. 97223
14.5%
5 73918
11.1%
4 63625
9.5%
6 53034
7.9%
2 51820
7.8%
1 45628
 
6.8%
9 41949
 
6.3%
7 40707
 
6.1%
8 36804
 
5.5%
Other values (2) 35610
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 668221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 127903
19.1%
. 97223
14.5%
5 73918
11.1%
4 63625
9.5%
6 53034
7.9%
2 51820
7.8%
1 45628
 
6.8%
9 41949
 
6.3%
7 40707
 
6.1%
8 36804
 
5.5%
Other values (2) 35610
 
5.3%

decimalLongitude
Text

Missing 

Distinct27083
Distinct (%)27.9%
Missing6513
Missing (%)6.3%
Memory size810.6 KiB
2025-01-23T18:15:04.035281image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.899273842
Min length3

Characters and Unicode

Total characters767999
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13950 ?
Unique (%)14.3%

Sample

1st row102.2471
2nd row-74.538
3rd row-83.0765
4th row-82.2367
5th row-78.4689
ValueCountFrequency (%)
81.6657 1632
 
1.7%
81.7785 761
 
0.8%
78.6388 598
 
0.6%
81.6703 340
 
0.3%
81.6648 257
 
0.3%
81.7819 228
 
0.2%
81.8726 223
 
0.2%
83.1968 221
 
0.2%
79.3987 221
 
0.2%
78.9055 213
 
0.2%
Other values (27065) 92530
95.2%
2025-01-23T18:15:04.314935image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 99653
13.0%
8 97452
12.7%
. 97220
12.7%
- 92301
12.0%
1 58906
7.7%
9 55787
7.3%
2 49346
6.4%
6 49327
6.4%
3 48369
6.3%
5 44851
5.8%
Other values (9) 74787
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 578465
75.3%
Other Punctuation 97220
 
12.7%
Dash Punctuation 92301
 
12.0%
Uppercase Letter 13
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 99653
17.2%
8 97452
16.8%
1 58906
10.2%
9 55787
9.6%
2 49346
8.5%
6 49327
8.5%
3 48369
8.4%
5 44851
7.8%
0 38352
 
6.6%
4 36422
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
W 3
23.1%
G 3
23.1%
S 3
23.1%
H 1
 
7.7%
E 1
 
7.7%
R 1
 
7.7%
P 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 97220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 767986
> 99.9%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
7 99653
13.0%
8 97452
12.7%
. 97220
12.7%
- 92301
12.0%
1 58906
7.7%
9 55787
7.3%
2 49346
6.4%
6 49327
6.4%
3 48369
6.3%
5 44851
5.8%
Other values (2) 74774
9.7%
Latin
ValueCountFrequency (%)
W 3
23.1%
G 3
23.1%
S 3
23.1%
H 1
 
7.7%
E 1
 
7.7%
R 1
 
7.7%
P 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 767999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 99653
13.0%
8 97452
12.7%
. 97220
12.7%
- 92301
12.0%
1 58906
7.7%
9 55787
7.3%
2 49346
6.4%
6 49327
6.4%
3 48369
6.3%
5 44851
5.8%
Other values (9) 74787
9.7%

geodeticDatum
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing2328
Missing (%)2.2%
Memory size810.6 KiB
2025-01-23T18:15:04.375141image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.999940834
Min length3

Characters and Unicode

Total characters507039
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS84
2nd rowWGS84
3rd rowWGS84
4th rowWGS84
5th rowWGS84
ValueCountFrequency (%)
wgs84 101406
> 99.9%
805 3
 
< 0.1%
2025-01-23T18:15:04.483804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 101409
20.0%
W 101406
20.0%
G 101406
20.0%
S 101406
20.0%
4 101406
20.0%
0 3
 
< 0.1%
5 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 304218
60.0%
Decimal Number 202821
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 101409
50.0%
4 101406
50.0%
0 3
 
< 0.1%
5 3
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
W 101406
33.3%
G 101406
33.3%
S 101406
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 304218
60.0%
Common 202821
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 101409
50.0%
4 101406
50.0%
0 3
 
< 0.1%
5 3
 
< 0.1%
Latin
ValueCountFrequency (%)
W 101406
33.3%
G 101406
33.3%
S 101406
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 507039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 101409
20.0%
W 101406
20.0%
G 101406
20.0%
S 101406
20.0%
4 101406
20.0%
0 3
 
< 0.1%
5 3
 
< 0.1%

coordinateUncertaintyInMeters
Text

Missing 

Distinct8
Distinct (%)< 0.1%
Missing22047
Missing (%)21.3%
Memory size810.6 KiB
2025-01-23T18:15:04.531766image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.306965357
Min length3

Characters and Unicode

Total characters270146
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row805
2nd row402
3rd row201
4th row201
5th row805
ValueCountFrequency (%)
201 28933
35.4%
402 19345
23.7%
805 12142
14.9%
1609 9301
 
11.4%
4023 6558
 
8.0%
12070 3172
 
3.9%
4828 1605
 
2.0%
20117 634
 
0.8%
2025-01-23T18:15:04.650455image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83257
30.8%
2 60247
22.3%
1 42674
15.8%
4 27508
 
10.2%
8 15352
 
5.7%
5 12142
 
4.5%
6 9301
 
3.4%
9 9301
 
3.4%
3 6558
 
2.4%
7 3806
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270146
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83257
30.8%
2 60247
22.3%
1 42674
15.8%
4 27508
 
10.2%
8 15352
 
5.7%
5 12142
 
4.5%
6 9301
 
3.4%
9 9301
 
3.4%
3 6558
 
2.4%
7 3806
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 270146
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83257
30.8%
2 60247
22.3%
1 42674
15.8%
4 27508
 
10.2%
8 15352
 
5.7%
5 12142
 
4.5%
6 9301
 
3.4%
9 9301
 
3.4%
3 6558
 
2.4%
7 3806
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83257
30.8%
2 60247
22.3%
1 42674
15.8%
4 27508
 
10.2%
8 15352
 
5.7%
5 12142
 
4.5%
6 9301
 
3.4%
9 9301
 
3.4%
3 6558
 
2.4%
7 3806
 
1.4%

verbatimCoordinates
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:04.694619image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1954
ValueCountFrequency (%)
1954 1
100.0%
2025-01-23T18:15:04.788067image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
4 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
4 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
4 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
4 1
25.0%

verbatimLatitude
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:04.829545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row04
ValueCountFrequency (%)
04 1
100.0%
2025-01-23T18:15:04.923576image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
50.0%
4 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
50.0%
4 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
50.0%
4 1
50.0%

verbatimLongitude
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:04.965569image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row7
ValueCountFrequency (%)
7 1
100.0%
2025-01-23T18:15:05.059725image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1
100.0%

footprintSRS
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:05.104799image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowBufo quercicus
ValueCountFrequency (%)
bufo 1
50.0%
quercicus 1
50.0%
2025-01-23T18:15:05.206583image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 3
21.4%
c 2
14.3%
B 1
 
7.1%
f 1
 
7.1%
o 1
 
7.1%
1
 
7.1%
q 1
 
7.1%
e 1
 
7.1%
r 1
 
7.1%
i 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
85.7%
Uppercase Letter 1
 
7.1%
Space Separator 1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 3
25.0%
c 2
16.7%
f 1
 
8.3%
o 1
 
8.3%
q 1
 
8.3%
e 1
 
8.3%
r 1
 
8.3%
i 1
 
8.3%
s 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
92.9%
Common 1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 3
23.1%
c 2
15.4%
B 1
 
7.7%
f 1
 
7.7%
o 1
 
7.7%
q 1
 
7.7%
e 1
 
7.7%
r 1
 
7.7%
i 1
 
7.7%
s 1
 
7.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 3
21.4%
c 2
14.3%
B 1
 
7.1%
f 1
 
7.1%
o 1
 
7.1%
1
 
7.1%
q 1
 
7.1%
e 1
 
7.1%
r 1
 
7.1%
i 1
 
7.1%

footprintSpatialFit
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:05.260757image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length22.5
Mean length22.5
Min length22

Characters and Unicode

Total characters45
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDesmognathus monticola
2nd rowDesmognathus cf. fuscus
ValueCountFrequency (%)
desmognathus 2
40.0%
monticola 1
20.0%
cf 1
20.0%
fuscus 1
20.0%
2025-01-23T18:15:05.372266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 6
13.3%
u 4
 
8.9%
o 4
 
8.9%
t 3
 
6.7%
m 3
 
6.7%
n 3
 
6.7%
a 3
 
6.7%
c 3
 
6.7%
3
 
6.7%
f 2
 
4.4%
Other values (7) 11
24.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
86.7%
Space Separator 3
 
6.7%
Uppercase Letter 2
 
4.4%
Other Punctuation 1
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 6
15.4%
u 4
10.3%
o 4
10.3%
t 3
7.7%
m 3
7.7%
n 3
7.7%
a 3
7.7%
c 3
7.7%
f 2
 
5.1%
h 2
 
5.1%
Other values (4) 6
15.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41
91.1%
Common 4
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 6
14.6%
u 4
9.8%
o 4
9.8%
t 3
 
7.3%
m 3
 
7.3%
n 3
 
7.3%
a 3
 
7.3%
c 3
 
7.3%
f 2
 
4.9%
D 2
 
4.9%
Other values (5) 8
19.5%
Common
ValueCountFrequency (%)
3
75.0%
. 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 6
13.3%
u 4
 
8.9%
o 4
 
8.9%
t 3
 
6.7%
m 3
 
6.7%
n 3
 
6.7%
a 3
 
6.7%
c 3
 
6.7%
3
 
6.7%
f 2
 
4.4%
Other values (7) 11
24.4%

georeferenceProtocol
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:05.420667image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters66
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPersonal Communication
2nd rowPersonal Communication
3rd rowPersonal Communication
ValueCountFrequency (%)
personal 3
50.0%
communication 3
50.0%
2025-01-23T18:15:05.523806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 9
13.6%
n 9
13.6%
a 6
 
9.1%
m 6
 
9.1%
i 6
 
9.1%
P 3
 
4.5%
e 3
 
4.5%
r 3
 
4.5%
s 3
 
4.5%
l 3
 
4.5%
Other values (5) 15
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57
86.4%
Uppercase Letter 6
 
9.1%
Space Separator 3
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9
15.8%
n 9
15.8%
a 6
10.5%
m 6
10.5%
i 6
10.5%
e 3
 
5.3%
r 3
 
5.3%
s 3
 
5.3%
l 3
 
5.3%
u 3
 
5.3%
Other values (2) 6
10.5%
Uppercase Letter
ValueCountFrequency (%)
P 3
50.0%
C 3
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
95.5%
Common 3
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 9
14.3%
n 9
14.3%
a 6
9.5%
m 6
9.5%
i 6
9.5%
P 3
 
4.8%
e 3
 
4.8%
r 3
 
4.8%
s 3
 
4.8%
l 3
 
4.8%
Other values (4) 12
19.0%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 9
13.6%
n 9
13.6%
a 6
 
9.1%
m 6
 
9.1%
i 6
 
9.1%
P 3
 
4.5%
e 3
 
4.5%
r 3
 
4.5%
s 3
 
4.5%
l 3
 
4.5%
Other values (5) 15
22.7%

georeferenceSources
Text

Missing 

Distinct552
Distinct (%)0.5%
Missing1367
Missing (%)1.3%
Memory size810.6 KiB
2025-01-23T18:15:05.670460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length50
Median length49
Mean length14.76497997
Min length3

Characters and Unicode

Total characters1511491
Distinct characters74
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)0.2%

Sample

1st rowGPS
2nd rowDeLorme
3rd rowDelorme Topo North America 9.0
4th rowGoogle Maps
5th rowGoogle Maps
ValueCountFrequency (%)
delorme 45862
18.9%
google 37091
15.3%
maps 35615
14.7%
topo 15490
 
6.4%
north 10676
 
4.4%
america 10646
 
4.4%
9.0 9341
 
3.9%
gps 8212
 
3.4%
acme 6949
 
2.9%
mapper 6943
 
2.9%
Other values (370) 55275
22.8%
2025-01-23T18:15:05.897335image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 194390
 
12.9%
e 170274
 
11.3%
139735
 
9.2%
r 90736
 
6.0%
a 75872
 
5.0%
p 74615
 
4.9%
m 65023
 
4.3%
M 54536
 
3.6%
l 54328
 
3.6%
s 48329
 
3.2%
Other values (64) 543653
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 950279
62.9%
Uppercase Letter 326145
 
21.6%
Space Separator 139735
 
9.2%
Decimal Number 51187
 
3.4%
Other Punctuation 40978
 
2.7%
Dash Punctuation 1846
 
0.1%
Connector Punctuation 1062
 
0.1%
Open Punctuation 129
 
< 0.1%
Close Punctuation 129
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 194390
20.5%
e 170274
17.9%
r 90736
9.5%
a 75872
 
8.0%
p 74615
 
7.9%
m 65023
 
6.8%
l 54328
 
5.7%
s 48329
 
5.1%
g 45106
 
4.7%
i 26546
 
2.8%
Other values (16) 105060
11.1%
Uppercase Letter
ValueCountFrequency (%)
M 54536
16.7%
D 47836
14.7%
G 47077
14.4%
L 44357
13.6%
A 22598
6.9%
T 21659
 
6.6%
S 16194
 
5.0%
C 15837
 
4.9%
N 15784
 
4.8%
P 11732
 
3.6%
Other values (13) 28535
8.7%
Decimal Number
ValueCountFrequency (%)
0 15615
30.5%
2 13721
26.8%
9 11031
21.6%
6 5636
 
11.0%
1 2652
 
5.2%
3 912
 
1.8%
8 870
 
1.7%
4 571
 
1.1%
5 100
 
0.2%
7 79
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 27043
66.0%
, 10851
26.5%
/ 2493
 
6.1%
: 508
 
1.2%
; 80
 
0.2%
' 2
 
< 0.1%
? 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 78
60.5%
[ 51
39.5%
Close Punctuation
ValueCountFrequency (%)
) 78
60.5%
] 51
39.5%
Space Separator
ValueCountFrequency (%)
139735
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1846
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1062
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1276424
84.4%
Common 235067
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 194390
15.2%
e 170274
13.3%
r 90736
 
7.1%
a 75872
 
5.9%
p 74615
 
5.8%
m 65023
 
5.1%
M 54536
 
4.3%
l 54328
 
4.3%
s 48329
 
3.8%
D 47836
 
3.7%
Other values (39) 400485
31.4%
Common
ValueCountFrequency (%)
139735
59.4%
. 27043
 
11.5%
0 15615
 
6.6%
2 13721
 
5.8%
9 11031
 
4.7%
, 10851
 
4.6%
6 5636
 
2.4%
1 2652
 
1.1%
/ 2493
 
1.1%
- 1846
 
0.8%
Other values (15) 4444
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1511491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 194390
 
12.9%
e 170274
 
11.3%
139735
 
9.2%
r 90736
 
6.0%
a 75872
 
5.0%
p 74615
 
4.9%
m 65023
 
4.3%
M 54536
 
3.6%
l 54328
 
3.6%
s 48329
 
3.2%
Other values (64) 543653
36.0%

earliestEonOrLowestEonothem
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:05.952687image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length10.5
Min length8

Characters and Unicode

Total characters21
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAnimalia
2nd rowNorth America
ValueCountFrequency (%)
animalia 1
33.3%
north 1
33.3%
america 1
33.3%
2025-01-23T18:15:06.053627image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3
14.3%
a 3
14.3%
A 2
9.5%
m 2
9.5%
r 2
9.5%
n 1
 
4.8%
l 1
 
4.8%
N 1
 
4.8%
o 1
 
4.8%
t 1
 
4.8%
Other values (4) 4
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17
81.0%
Uppercase Letter 3
 
14.3%
Space Separator 1
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3
17.6%
a 3
17.6%
m 2
11.8%
r 2
11.8%
n 1
 
5.9%
l 1
 
5.9%
o 1
 
5.9%
t 1
 
5.9%
h 1
 
5.9%
e 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
95.2%
Common 1
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3
15.0%
a 3
15.0%
A 2
10.0%
m 2
10.0%
r 2
10.0%
n 1
 
5.0%
l 1
 
5.0%
N 1
 
5.0%
o 1
 
5.0%
t 1
 
5.0%
Other values (3) 3
15.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3
14.3%
a 3
14.3%
A 2
9.5%
m 2
9.5%
r 2
9.5%
n 1
 
4.8%
l 1
 
4.8%
N 1
 
4.8%
o 1
 
4.8%
t 1
 
4.8%
Other values (4) 4
19.0%

latestEonOrHighestEonothem
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.099344image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowChordata
2nd rowAnimalia
3rd rowAnimalia
ValueCountFrequency (%)
animalia 2
66.7%
chordata 1
33.3%
2025-01-23T18:15:06.197799image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6
25.0%
i 4
16.7%
A 2
 
8.3%
n 2
 
8.3%
m 2
 
8.3%
l 2
 
8.3%
C 1
 
4.2%
h 1
 
4.2%
o 1
 
4.2%
r 1
 
4.2%
Other values (2) 2
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21
87.5%
Uppercase Letter 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6
28.6%
i 4
19.0%
n 2
 
9.5%
m 2
 
9.5%
l 2
 
9.5%
h 1
 
4.8%
o 1
 
4.8%
r 1
 
4.8%
d 1
 
4.8%
t 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6
25.0%
i 4
16.7%
A 2
 
8.3%
n 2
 
8.3%
m 2
 
8.3%
l 2
 
8.3%
C 1
 
4.2%
h 1
 
4.2%
o 1
 
4.2%
r 1
 
4.2%
Other values (2) 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6
25.0%
i 4
16.7%
A 2
 
8.3%
n 2
 
8.3%
m 2
 
8.3%
l 2
 
8.3%
C 1
 
4.2%
h 1
 
4.2%
o 1
 
4.2%
r 1
 
4.2%
Other values (2) 2
 
8.3%

earliestEraOrLowestErathem
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.241313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowAMPHIBIA
2nd rowChordata
3rd rowChordata
ValueCountFrequency (%)
chordata 2
66.7%
amphibia 1
33.3%
2025-01-23T18:15:06.341513image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
16.7%
C 2
8.3%
h 2
8.3%
o 2
8.3%
r 2
8.3%
d 2
8.3%
t 2
8.3%
A 2
8.3%
I 2
8.3%
M 1
 
4.2%
Other values (3) 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
58.3%
Uppercase Letter 10
41.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
A 2
20.0%
I 2
20.0%
M 1
10.0%
P 1
10.0%
H 1
10.0%
B 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
a 4
28.6%
h 2
14.3%
o 2
14.3%
r 2
14.3%
d 2
14.3%
t 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
16.7%
C 2
8.3%
h 2
8.3%
o 2
8.3%
r 2
8.3%
d 2
8.3%
t 2
8.3%
A 2
8.3%
I 2
8.3%
M 1
 
4.2%
Other values (3) 3
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
16.7%
C 2
8.3%
h 2
8.3%
o 2
8.3%
r 2
8.3%
d 2
8.3%
t 2
8.3%
A 2
8.3%
I 2
8.3%
M 1
 
4.2%
Other values (3) 3
12.5%

latestEraOrHighestErathem
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.388192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length6.5
Mean length6.5
Min length5

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAnura
2nd rowAMPHIBIA
ValueCountFrequency (%)
anura 1
50.0%
amphibia 1
50.0%
2025-01-23T18:15:06.499375image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 3
23.1%
I 2
15.4%
n 1
 
7.7%
u 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%
M 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
B 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9
69.2%
Lowercase Letter 4
30.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3
33.3%
I 2
22.2%
M 1
 
11.1%
P 1
 
11.1%
H 1
 
11.1%
B 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
n 1
25.0%
u 1
25.0%
r 1
25.0%
a 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3
23.1%
I 2
15.4%
n 1
 
7.7%
u 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%
M 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
B 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3
23.1%
I 2
15.4%
n 1
 
7.7%
u 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%
M 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
B 1
 
7.7%

earliestPeriodOrLowestSystem
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.546632image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10
Min length7

Characters and Unicode

Total characters20
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowCaudata
2nd rowUnited States
ValueCountFrequency (%)
caudata 1
33.3%
united 1
33.3%
states 1
33.3%
2025-01-23T18:15:06.655471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
20.0%
t 4
20.0%
d 2
10.0%
e 2
10.0%
C 1
 
5.0%
u 1
 
5.0%
U 1
 
5.0%
n 1
 
5.0%
i 1
 
5.0%
1
 
5.0%
Other values (2) 2
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
80.0%
Uppercase Letter 3
 
15.0%
Space Separator 1
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
25.0%
t 4
25.0%
d 2
12.5%
e 2
12.5%
u 1
 
6.2%
n 1
 
6.2%
i 1
 
6.2%
s 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
U 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19
95.0%
Common 1
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
21.1%
t 4
21.1%
d 2
10.5%
e 2
10.5%
C 1
 
5.3%
u 1
 
5.3%
U 1
 
5.3%
n 1
 
5.3%
i 1
 
5.3%
S 1
 
5.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
20.0%
t 4
20.0%
d 2
10.0%
e 2
10.0%
C 1
 
5.0%
u 1
 
5.0%
U 1
 
5.0%
n 1
 
5.0%
i 1
 
5.0%
1
 
5.0%
Other values (2) 2
10.0%

latestPeriodOrHighestSystem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.701370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowBufonidae
ValueCountFrequency (%)
bufonidae 1
100.0%
2025-01-23T18:15:06.796453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 1
11.1%
u 1
11.1%
f 1
11.1%
o 1
11.1%
n 1
11.1%
i 1
11.1%
d 1
11.1%
a 1
11.1%
e 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
88.9%
Uppercase Letter 1
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 1
12.5%
f 1
12.5%
o 1
12.5%
n 1
12.5%
i 1
12.5%
d 1
12.5%
a 1
12.5%
e 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 1
11.1%
u 1
11.1%
f 1
11.1%
o 1
11.1%
n 1
11.1%
i 1
11.1%
d 1
11.1%
a 1
11.1%
e 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 1
11.1%
u 1
11.1%
f 1
11.1%
o 1
11.1%
n 1
11.1%
i 1
11.1%
d 1
11.1%
a 1
11.1%
e 1
11.1%

earliestEpochOrLowestSeries
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.847432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters28
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPlethodontidae
2nd rowSouth Carolina
ValueCountFrequency (%)
plethodontidae 1
33.3%
south 1
33.3%
carolina 1
33.3%
2025-01-23T18:15:06.949897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 4
14.3%
t 3
10.7%
a 3
10.7%
l 2
 
7.1%
e 2
 
7.1%
h 2
 
7.1%
d 2
 
7.1%
n 2
 
7.1%
i 2
 
7.1%
P 1
 
3.6%
Other values (5) 5
17.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
85.7%
Uppercase Letter 3
 
10.7%
Space Separator 1
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
16.7%
t 3
12.5%
a 3
12.5%
l 2
8.3%
e 2
8.3%
h 2
8.3%
d 2
8.3%
n 2
8.3%
i 2
8.3%
u 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
S 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27
96.4%
Common 1
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
14.8%
t 3
11.1%
a 3
11.1%
l 2
7.4%
e 2
7.4%
h 2
7.4%
d 2
7.4%
n 2
7.4%
i 2
7.4%
P 1
 
3.7%
Other values (4) 4
14.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 4
14.3%
t 3
10.7%
a 3
10.7%
l 2
 
7.1%
e 2
 
7.1%
h 2
 
7.1%
d 2
 
7.1%
n 2
 
7.1%
i 2
 
7.1%
P 1
 
3.6%
Other values (5) 5
17.9%

latestEpochOrHighestSeries
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:06.995537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowSaluda
ValueCountFrequency (%)
saluda 1
100.0%
2025-01-23T18:15:07.090343image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
33.3%
S 1
16.7%
l 1
16.7%
u 1
16.7%
d 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5
83.3%
Uppercase Letter 1
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2
40.0%
l 1
20.0%
u 1
20.0%
d 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2
33.3%
S 1
16.7%
l 1
16.7%
u 1
16.7%
d 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2
33.3%
S 1
16.7%
l 1
16.7%
u 1
16.7%
d 1
16.7%

latestAgeOrHighestStage
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:07.138766image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length15.5
Mean length15.5
Min length4

Characters and Unicode

Total characters31
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowBufo
2nd row[No further locality data].
ValueCountFrequency (%)
bufo 1
20.0%
no 1
20.0%
further 1
20.0%
locality 1
20.0%
data 1
20.0%
2025-01-23T18:15:07.242771image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
 
9.7%
o 3
 
9.7%
3
 
9.7%
t 3
 
9.7%
f 2
 
6.5%
r 2
 
6.5%
u 2
 
6.5%
l 2
 
6.5%
B 1
 
3.2%
] 1
 
3.2%
Other values (9) 9
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23
74.2%
Space Separator 3
 
9.7%
Uppercase Letter 2
 
6.5%
Close Punctuation 1
 
3.2%
Open Punctuation 1
 
3.2%
Other Punctuation 1
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3
13.0%
o 3
13.0%
t 3
13.0%
f 2
8.7%
r 2
8.7%
u 2
8.7%
l 2
8.7%
d 1
 
4.3%
y 1
 
4.3%
i 1
 
4.3%
Other values (3) 3
13.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25
80.6%
Common 6
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3
12.0%
o 3
12.0%
t 3
12.0%
f 2
 
8.0%
r 2
 
8.0%
u 2
 
8.0%
l 2
 
8.0%
B 1
 
4.0%
d 1
 
4.0%
y 1
 
4.0%
Other values (5) 5
20.0%
Common
ValueCountFrequency (%)
3
50.0%
] 1
 
16.7%
[ 1
 
16.7%
. 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3
 
9.7%
o 3
 
9.7%
3
 
9.7%
t 3
 
9.7%
f 2
 
6.5%
r 2
 
6.5%
u 2
 
6.5%
l 2
 
6.5%
B 1
 
3.2%
] 1
 
3.2%
Other values (9) 9
29.0%

lowestBiostratigraphicZone
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:07.292094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDesmognathus
2nd rowDesmognathus
ValueCountFrequency (%)
desmognathus 2
100.0%
2025-01-23T18:15:07.506528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
16.7%
D 2
8.3%
e 2
8.3%
m 2
8.3%
o 2
8.3%
g 2
8.3%
n 2
8.3%
a 2
8.3%
t 2
8.3%
h 2
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22
91.7%
Uppercase Letter 2
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
18.2%
e 2
9.1%
m 2
9.1%
o 2
9.1%
g 2
9.1%
n 2
9.1%
a 2
9.1%
t 2
9.1%
h 2
9.1%
u 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
16.7%
D 2
8.3%
e 2
8.3%
m 2
8.3%
o 2
8.3%
g 2
8.3%
n 2
8.3%
a 2
8.3%
t 2
8.3%
h 2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
16.7%
D 2
8.3%
e 2
8.3%
m 2
8.3%
o 2
8.3%
g 2
8.3%
n 2
8.3%
a 2
8.3%
t 2
8.3%
h 2
8.3%

group
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:07.549591image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowquercicus
ValueCountFrequency (%)
quercicus 1
100.0%
2025-01-23T18:15:07.649546image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 2
22.2%
c 2
22.2%
q 1
11.1%
e 1
11.1%
r 1
11.1%
i 1
11.1%
s 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 2
22.2%
c 2
22.2%
q 1
11.1%
e 1
11.1%
r 1
11.1%
i 1
11.1%
s 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 2
22.2%
c 2
22.2%
q 1
11.1%
e 1
11.1%
r 1
11.1%
i 1
11.1%
s 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 2
22.2%
c 2
22.2%
q 1
11.1%
e 1
11.1%
r 1
11.1%
i 1
11.1%
s 1
11.1%

formation
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:07.698614image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length9.5
Min length9

Characters and Unicode

Total characters19
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowmonticola
2nd rowcf. fuscus
ValueCountFrequency (%)
monticola 1
33.3%
cf 1
33.3%
fuscus 1
33.3%
2025-01-23T18:15:07.807775image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 3
15.8%
o 2
10.5%
f 2
10.5%
u 2
10.5%
s 2
10.5%
m 1
 
5.3%
n 1
 
5.3%
t 1
 
5.3%
i 1
 
5.3%
l 1
 
5.3%
Other values (3) 3
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17
89.5%
Other Punctuation 1
 
5.3%
Space Separator 1
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 3
17.6%
o 2
11.8%
f 2
11.8%
u 2
11.8%
s 2
11.8%
m 1
 
5.9%
n 1
 
5.9%
t 1
 
5.9%
i 1
 
5.9%
l 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17
89.5%
Common 2
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 3
17.6%
o 2
11.8%
f 2
11.8%
u 2
11.8%
s 2
11.8%
m 1
 
5.9%
n 1
 
5.9%
t 1
 
5.9%
i 1
 
5.9%
l 1
 
5.9%
Common
ValueCountFrequency (%)
. 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 3
15.8%
o 2
10.5%
f 2
10.5%
u 2
10.5%
s 2
10.5%
m 1
 
5.3%
n 1
 
5.3%
t 1
 
5.3%
i 1
 
5.3%
l 1
 
5.3%
Other values (3) 3
15.8%

bed
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:07.858465image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters15
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowspecificEpithet
ValueCountFrequency (%)
specificepithet 1
100.0%
2025-01-23T18:15:07.959845image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3
20.0%
p 2
13.3%
e 2
13.3%
c 2
13.3%
t 2
13.3%
s 1
 
6.7%
f 1
 
6.7%
E 1
 
6.7%
h 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
93.3%
Uppercase Letter 1
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3
21.4%
p 2
14.3%
e 2
14.3%
c 2
14.3%
t 2
14.3%
s 1
 
7.1%
f 1
 
7.1%
h 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3
20.0%
p 2
13.3%
e 2
13.3%
c 2
13.3%
t 2
13.3%
s 1
 
6.7%
f 1
 
6.7%
E 1
 
6.7%
h 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3
20.0%
p 2
13.3%
e 2
13.3%
c 2
13.3%
t 2
13.3%
s 1
 
6.7%
f 1
 
6.7%
E 1
 
6.7%
h 1
 
6.7%

identificationID
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing103735
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.011570image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters30
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspecificEpithet
2nd rowspecificEpithet
ValueCountFrequency (%)
specificepithet 2
100.0%
2025-01-23T18:15:08.112283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 6
20.0%
p 4
13.3%
e 4
13.3%
c 4
13.3%
t 4
13.3%
s 2
 
6.7%
f 2
 
6.7%
E 2
 
6.7%
h 2
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28
93.3%
Uppercase Letter 2
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 6
21.4%
p 4
14.3%
e 4
14.3%
c 4
14.3%
t 4
14.3%
s 2
 
7.1%
f 2
 
7.1%
h 2
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 6
20.0%
p 4
13.3%
e 4
13.3%
c 4
13.3%
t 4
13.3%
s 2
 
6.7%
f 2
 
6.7%
E 2
 
6.7%
h 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 6
20.0%
p 4
13.3%
e 4
13.3%
c 4
13.3%
t 4
13.3%
s 2
 
6.7%
f 2
 
6.7%
E 2
 
6.7%
h 2
 
6.7%

identificationQualifier
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.157823image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOak Toad
ValueCountFrequency (%)
oak 1
50.0%
toad 1
50.0%
2025-01-23T18:15:08.263753image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
25.0%
O 1
12.5%
k 1
12.5%
1
12.5%
T 1
12.5%
o 1
12.5%
d 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5
62.5%
Uppercase Letter 2
 
25.0%
Space Separator 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2
40.0%
k 1
20.0%
o 1
20.0%
d 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7
87.5%
Common 1
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2
28.6%
O 1
14.3%
k 1
14.3%
T 1
14.3%
o 1
14.3%
d 1
14.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2
25.0%
O 1
12.5%
k 1
12.5%
1
12.5%
T 1
12.5%
o 1
12.5%
d 1
12.5%

typeStatus
Text

Missing 

Distinct5
Distinct (%)1.5%
Missing103407
Missing (%)99.7%
Memory size810.6 KiB
2025-01-23T18:15:08.314105image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.009090909
Min length7

Characters and Unicode

Total characters2643
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowparatype
2nd rowparatype
3rd rowholotype
4th rowparatype
5th rowparatype
ValueCountFrequency (%)
paratype 303
91.5%
holotype 19
 
5.7%
neotype 4
 
1.2%
allotype 3
 
0.9%
seal 1
 
0.3%
salamander 1
 
0.3%
2025-01-23T18:15:08.433257image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
p 632
23.9%
a 613
23.2%
e 335
12.7%
t 329
12.4%
y 329
12.4%
r 304
11.5%
o 45
 
1.7%
l 27
 
1.0%
h 19
 
0.7%
n 5
 
0.2%
Other values (4) 5
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2640
99.9%
Uppercase Letter 2
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 632
23.9%
a 613
23.2%
e 335
12.7%
t 329
12.5%
y 329
12.5%
r 304
11.5%
o 45
 
1.7%
l 27
 
1.0%
h 19
 
0.7%
n 5
 
0.2%
Other values (2) 2
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2642
> 99.9%
Common 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 632
23.9%
a 613
23.2%
e 335
12.7%
t 329
12.5%
y 329
12.5%
r 304
11.5%
o 45
 
1.7%
l 27
 
1.0%
h 19
 
0.7%
n 5
 
0.2%
Other values (3) 4
 
0.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 632
23.9%
a 613
23.2%
e 335
12.7%
t 329
12.4%
y 329
12.4%
r 304
11.5%
o 45
 
1.7%
l 27
 
1.0%
h 19
 
0.7%
n 5
 
0.2%
Other values (4) 5
 
0.2%

identifiedByID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.478418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row34.0015
ValueCountFrequency (%)
34.0015 1
100.0%
2025-01-23T18:15:08.573638image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
28.6%
3 1
14.3%
4 1
14.3%
. 1
14.3%
1 1
14.3%
5 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
85.7%
Other Punctuation 1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
33.3%
3 1
16.7%
4 1
16.7%
1 1
16.7%
5 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
28.6%
3 1
14.3%
4 1
14.3%
. 1
14.3%
1 1
14.3%
5 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
28.6%
3 1
14.3%
4 1
14.3%
. 1
14.3%
1 1
14.3%
5 1
14.3%

dateIdentified
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.616315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row-81.7721
ValueCountFrequency (%)
81.7721 1
100.0%
2025-01-23T18:15:08.713694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
25.0%
7 2
25.0%
- 1
12.5%
8 1
12.5%
. 1
12.5%
2 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
75.0%
Dash Punctuation 1
 
12.5%
Other Punctuation 1
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
33.3%
7 2
33.3%
8 1
16.7%
2 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
25.0%
7 2
25.0%
- 1
12.5%
8 1
12.5%
. 1
12.5%
2 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
25.0%
7 2
25.0%
- 1
12.5%
8 1
12.5%
. 1
12.5%
2 1
12.5%

identificationReferences
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.758188image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowWGS84
ValueCountFrequency (%)
wgs84 1
100.0%
2025-01-23T18:15:08.852433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
60.0%
Decimal Number 2
40.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 1
33.3%
G 1
33.3%
S 1
33.3%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
60.0%
Common 2
40.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 1
33.3%
G 1
33.3%
S 1
33.3%
Common
ValueCountFrequency (%)
8 1
50.0%
4 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W 1
20.0%
G 1
20.0%
S 1
20.0%
8 1
20.0%
4 1
20.0%

taxonConceptID
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:08.903208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters57
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPseudacris brimleyi
2nd rowPseudacris brimleyi
3rd rowPseudacris brimleyi
ValueCountFrequency (%)
pseudacris 3
50.0%
brimleyi 3
50.0%
2025-01-23T18:15:09.011156image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 9
15.8%
s 6
10.5%
e 6
10.5%
r 6
10.5%
P 3
 
5.3%
u 3
 
5.3%
d 3
 
5.3%
a 3
 
5.3%
c 3
 
5.3%
3
 
5.3%
Other values (4) 12
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51
89.5%
Uppercase Letter 3
 
5.3%
Space Separator 3
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 9
17.6%
s 6
11.8%
e 6
11.8%
r 6
11.8%
u 3
 
5.9%
d 3
 
5.9%
a 3
 
5.9%
c 3
 
5.9%
b 3
 
5.9%
m 3
 
5.9%
Other values (2) 6
11.8%
Uppercase Letter
ValueCountFrequency (%)
P 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54
94.7%
Common 3
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 9
16.7%
s 6
11.1%
e 6
11.1%
r 6
11.1%
P 3
 
5.6%
u 3
 
5.6%
d 3
 
5.6%
a 3
 
5.6%
c 3
 
5.6%
b 3
 
5.6%
Other values (3) 9
16.7%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 9
15.8%
s 6
10.5%
e 6
10.5%
r 6
10.5%
P 3
 
5.3%
u 3
 
5.3%
d 3
 
5.3%
a 3
 
5.3%
c 3
 
5.3%
3
 
5.3%
Other values (4) 12
21.1%

scientificName
Text

Distinct1647
Distinct (%)1.6%
Missing36
Missing (%)< 0.1%
Memory size810.6 KiB
2025-01-23T18:15:09.206685image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length49
Median length39
Mean length18.97056923
Min length4

Characters and Unicode

Total characters1967267
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique484 ?
Unique (%)0.5%

Sample

1st rowRhacophorus pachyproctus
2nd rowRana clamitans
3rd rowPlethodon glutinosus
4th rowDesmognathus monticola
5th rowLampropeltis triangulum elapsoides
ValueCountFrequency (%)
desmognathus 12827
 
6.0%
plethodon 8408
 
4.0%
rana 6409
 
3.0%
bufo 5881
 
2.8%
eurycea 4979
 
2.3%
pseudotriton 3386
 
1.6%
fuscus 3207
 
1.5%
nerodia 3010
 
1.4%
acris 3010
 
1.4%
pseudacris 3005
 
1.4%
Other values (1645) 157997
74.5%
2025-01-23T18:15:09.483241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 178286
 
9.1%
s 165529
 
8.4%
e 147249
 
7.5%
o 145010
 
7.4%
i 137590
 
7.0%
r 132814
 
6.8%
t 124414
 
6.3%
u 115445
 
5.9%
108418
 
5.5%
n 103054
 
5.2%
Other values (46) 609458
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1753046
89.1%
Space Separator 108419
 
5.5%
Uppercase Letter 103703
 
5.3%
Other Punctuation 2097
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 178286
10.2%
s 165529
 
9.4%
e 147249
 
8.4%
o 145010
 
8.3%
i 137590
 
7.8%
r 132814
 
7.6%
t 124414
 
7.1%
u 115445
 
6.6%
n 103054
 
5.9%
c 86389
 
4.9%
Other values (16) 417266
23.8%
Uppercase Letter
ValueCountFrequency (%)
P 16508
15.9%
D 14249
13.7%
A 9861
9.5%
E 9616
9.3%
R 7406
7.1%
N 7334
7.1%
S 6302
 
6.1%
C 6131
 
5.9%
B 6023
 
5.8%
H 4809
 
4.6%
Other values (13) 15464
14.9%
Other Punctuation
ValueCountFrequency (%)
. 2086
99.5%
? 10
 
0.5%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
108418
> 99.9%
  1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1856749
94.4%
Common 110518
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 178286
 
9.6%
s 165529
 
8.9%
e 147249
 
7.9%
o 145010
 
7.8%
i 137590
 
7.4%
r 132814
 
7.2%
t 124414
 
6.7%
u 115445
 
6.2%
n 103054
 
5.6%
c 86389
 
4.7%
Other values (39) 520969
28.1%
Common
ValueCountFrequency (%)
108418
98.1%
. 2086
 
1.9%
? 10
 
< 0.1%
  1
 
< 0.1%
/ 1
 
< 0.1%
[ 1
 
< 0.1%
] 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1967266
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 178286
 
9.1%
s 165529
 
8.4%
e 147249
 
7.5%
o 145010
 
7.4%
i 137590
 
7.0%
r 132814
 
6.8%
t 124414
 
6.3%
u 115445
 
5.9%
108418
 
5.5%
n 103054
 
5.2%
Other values (45) 609457
31.0%
None
ValueCountFrequency (%)
  1
100.0%

nameAccordingTo
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing103736
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:09.543303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDeLorme Topo USA 6.0
ValueCountFrequency (%)
delorme 1
25.0%
topo 1
25.0%
usa 1
25.0%
6.0 1
25.0%
2025-01-23T18:15:09.646739image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3
15.0%
3
15.0%
e 2
 
10.0%
D 1
 
5.0%
L 1
 
5.0%
r 1
 
5.0%
m 1
 
5.0%
T 1
 
5.0%
p 1
 
5.0%
U 1
 
5.0%
Other values (5) 5
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
40.0%
Uppercase Letter 6
30.0%
Space Separator 3
 
15.0%
Decimal Number 2
 
10.0%
Other Punctuation 1
 
5.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
L 1
16.7%
T 1
16.7%
U 1
16.7%
S 1
16.7%
A 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
o 3
37.5%
e 2
25.0%
r 1
 
12.5%
m 1
 
12.5%
p 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
70.0%
Common 6
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3
21.4%
e 2
14.3%
D 1
 
7.1%
L 1
 
7.1%
r 1
 
7.1%
m 1
 
7.1%
T 1
 
7.1%
p 1
 
7.1%
U 1
 
7.1%
S 1
 
7.1%
Common
ValueCountFrequency (%)
3
50.0%
6 1
 
16.7%
. 1
 
16.7%
0 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3
15.0%
3
15.0%
e 2
 
10.0%
D 1
 
5.0%
L 1
 
5.0%
r 1
 
5.0%
m 1
 
5.0%
T 1
 
5.0%
p 1
 
5.0%
U 1
 
5.0%
Other values (5) 5
25.0%

higherClassification
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:09.694555image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
ValueCountFrequency (%)
animalia 3
100.0%
2025-01-23T18:15:09.794789image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 6
25.0%
a 6
25.0%
A 3
12.5%
n 3
12.5%
m 3
12.5%
l 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21
87.5%
Uppercase Letter 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 6
28.6%
a 6
28.6%
n 3
14.3%
m 3
14.3%
l 3
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 6
25.0%
a 6
25.0%
A 3
12.5%
n 3
12.5%
m 3
12.5%
l 3
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 6
25.0%
a 6
25.0%
A 3
12.5%
n 3
12.5%
m 3
12.5%
l 3
12.5%

kingdom
Text

Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size810.6 KiB
2025-01-23T18:15:09.839832image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters829864
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 103730
> 99.9%
chordata 3
 
< 0.1%
2025-01-23T18:15:09.937118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 207466
25.0%
i 207460
25.0%
A 103730
12.5%
n 103730
12.5%
m 103730
12.5%
l 103730
12.5%
C 3
 
< 0.1%
h 3
 
< 0.1%
o 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 726131
87.5%
Uppercase Letter 103733
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 207466
28.6%
i 207460
28.6%
n 103730
14.3%
m 103730
14.3%
l 103730
14.3%
h 3
 
< 0.1%
o 3
 
< 0.1%
r 3
 
< 0.1%
d 3
 
< 0.1%
t 3
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
A 103730
> 99.9%
C 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 829864
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 207466
25.0%
i 207460
25.0%
A 103730
12.5%
n 103730
12.5%
m 103730
12.5%
l 103730
12.5%
C 3
 
< 0.1%
h 3
 
< 0.1%
o 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 829864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 207466
25.0%
i 207460
25.0%
A 103730
12.5%
n 103730
12.5%
m 103730
12.5%
l 103730
12.5%
C 3
 
< 0.1%
h 3
 
< 0.1%
o 3
 
< 0.1%
r 3
 
< 0.1%
Other values (2) 6
 
< 0.1%

phylum
Text

Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size810.6 KiB
2025-01-23T18:15:09.983612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters829864
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 103730
> 99.9%
amphibia 3
 
< 0.1%
2025-01-23T18:15:10.082978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 207460
25.0%
C 103730
12.5%
h 103730
12.5%
o 103730
12.5%
r 103730
12.5%
d 103730
12.5%
t 103730
12.5%
A 6
 
< 0.1%
I 6
 
< 0.1%
M 3
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 726110
87.5%
Uppercase Letter 103754
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 103730
> 99.9%
A 6
 
< 0.1%
I 6
 
< 0.1%
M 3
 
< 0.1%
P 3
 
< 0.1%
H 3
 
< 0.1%
B 3
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
a 207460
28.6%
h 103730
14.3%
o 103730
14.3%
r 103730
14.3%
d 103730
14.3%
t 103730
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 829864
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 207460
25.0%
C 103730
12.5%
h 103730
12.5%
o 103730
12.5%
r 103730
12.5%
d 103730
12.5%
t 103730
12.5%
A 6
 
< 0.1%
I 6
 
< 0.1%
M 3
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 829864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 207460
25.0%
C 103730
12.5%
h 103730
12.5%
o 103730
12.5%
r 103730
12.5%
d 103730
12.5%
t 103730
12.5%
A 6
 
< 0.1%
I 6
 
< 0.1%
M 3
 
< 0.1%
Other values (3) 9
 
< 0.1%

class
Text

Missing 

Distinct4
Distinct (%)< 0.1%
Missing5037
Missing (%)4.9%
Memory size810.6 KiB
2025-01-23T18:15:10.128234image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.999908815
Min length5

Characters and Unicode

Total characters789591
Distinct characters19
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAMPHIBIA
2nd rowAMPHIBIA
3rd rowAMPHIBIA
4th rowREPTILIA
5th rowREPTILIA
ValueCountFrequency (%)
amphibia 65201
66.1%
reptilia 33496
33.9%
anura 3
 
< 0.1%
2025-01-23T18:15:10.240354image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 197388
25.0%
A 163898
20.8%
P 98694
12.5%
H 65198
 
8.3%
B 65198
 
8.3%
M 65198
 
8.3%
T 33496
 
4.2%
L 33496
 
4.2%
E 33496
 
4.2%
R 33496
 
4.2%
Other values (9) 33
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 789558
> 99.9%
Lowercase Letter 33
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 197388
25.0%
A 163898
20.8%
P 98694
12.5%
H 65198
 
8.3%
B 65198
 
8.3%
M 65198
 
8.3%
T 33496
 
4.2%
L 33496
 
4.2%
E 33496
 
4.2%
R 33496
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
i 6
18.2%
a 6
18.2%
m 3
9.1%
p 3
9.1%
h 3
9.1%
b 3
9.1%
n 3
9.1%
u 3
9.1%
r 3
9.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 789591
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 197388
25.0%
A 163898
20.8%
P 98694
12.5%
H 65198
 
8.3%
B 65198
 
8.3%
M 65198
 
8.3%
T 33496
 
4.2%
L 33496
 
4.2%
E 33496
 
4.2%
R 33496
 
4.2%
Other values (9) 33
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 789591
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 197388
25.0%
A 163898
20.8%
P 98694
12.5%
H 65198
 
8.3%
B 65198
 
8.3%
M 65198
 
8.3%
T 33496
 
4.2%
L 33496
 
4.2%
E 33496
 
4.2%
R 33496
 
4.2%
Other values (9) 33
 
< 0.1%

order
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing3728
Missing (%)3.6%
Memory size810.6 KiB
2025-01-23T18:15:10.293477image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.933975942
Min length5

Characters and Unicode

Total characters693460
Distinct characters23
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnura
2nd rowAnura
3rd rowCaudata
4th rowCaudata
5th rowSquamata
ValueCountFrequency (%)
caudata 39901
39.9%
squamata 28557
28.6%
anura 25968
26.0%
testudines 5491
 
5.5%
crocodylia 67
 
0.1%
gymnophiona 23
 
< 0.1%
amphisbaenia 2
 
< 0.1%
2025-01-23T18:15:10.407719image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 231436
33.4%
u 99917
14.4%
t 73949
 
10.7%
d 45459
 
6.6%
C 39968
 
5.8%
n 31507
 
4.5%
m 28582
 
4.1%
S 28557
 
4.1%
q 28557
 
4.1%
r 26035
 
3.8%
Other values (13) 59493
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 593451
85.6%
Uppercase Letter 100009
 
14.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 231436
39.0%
u 99917
16.8%
t 73949
 
12.5%
d 45459
 
7.7%
n 31507
 
5.3%
m 28582
 
4.8%
q 28557
 
4.8%
r 26035
 
4.4%
e 10984
 
1.9%
s 10984
 
1.9%
Other values (8) 6041
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 39968
40.0%
S 28557
28.6%
A 25970
26.0%
T 5491
 
5.5%
G 23
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 693460
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 231436
33.4%
u 99917
14.4%
t 73949
 
10.7%
d 45459
 
6.6%
C 39968
 
5.8%
n 31507
 
4.5%
m 28582
 
4.1%
S 28557
 
4.1%
q 28557
 
4.1%
r 26035
 
3.8%
Other values (13) 59493
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 693460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 231436
33.4%
u 99917
14.4%
t 73949
 
10.7%
d 45459
 
6.6%
C 39968
 
5.8%
n 31507
 
4.5%
m 28582
 
4.1%
S 28557
 
4.1%
q 28557
 
4.1%
r 26035
 
3.8%
Other values (13) 59493
 
8.6%

superfamily
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:10.455259image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters21
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHylidae
2nd rowHylidae
3rd rowHylidae
ValueCountFrequency (%)
hylidae 3
100.0%
2025-01-23T18:15:10.558186image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 3
14.3%
y 3
14.3%
l 3
14.3%
i 3
14.3%
d 3
14.3%
a 3
14.3%
e 3
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
85.7%
Uppercase Letter 3
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
y 3
16.7%
l 3
16.7%
i 3
16.7%
d 3
16.7%
a 3
16.7%
e 3
16.7%
Uppercase Letter
ValueCountFrequency (%)
H 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 3
14.3%
y 3
14.3%
l 3
14.3%
i 3
14.3%
d 3
14.3%
a 3
14.3%
e 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 3
14.3%
y 3
14.3%
l 3
14.3%
i 3
14.3%
d 3
14.3%
a 3
14.3%
e 3
14.3%

family
Text

Missing 

Distinct91
Distinct (%)0.1%
Missing3728
Missing (%)3.6%
Memory size810.6 KiB
2025-01-23T18:15:10.629303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.99591037
Min length6

Characters and Unicode

Total characters1099690
Distinct characters39
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowRhacophoridae
2nd rowRanidae
3rd rowPlethodontidae
4th rowPlethodontidae
5th rowColubridae
ValueCountFrequency (%)
plethodontidae 31539
31.5%
colubridae 18313
18.3%
hylidae 8841
 
8.8%
ranidae 7118
 
7.1%
bufonidae 5819
 
5.8%
viperidae 3764
 
3.8%
emydidae 3062
 
3.1%
salamandridae 2989
 
3.0%
ambystomatidae 2598
 
2.6%
scincidae 2468
 
2.5%
Other values (81) 13498
13.5%
2025-01-23T18:15:10.767432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 142730
13.0%
d 138281
12.6%
a 122122
11.1%
i 111897
10.2%
o 103550
9.4%
t 74826
 
6.8%
l 66233
 
6.0%
n 56988
 
5.2%
h 38256
 
3.5%
P 35585
 
3.2%
Other values (29) 209222
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 999681
90.9%
Uppercase Letter 100009
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 142730
14.3%
d 138281
13.8%
a 122122
12.2%
i 111897
11.2%
o 103550
10.4%
t 74826
7.5%
l 66233
6.6%
n 56988
 
5.7%
h 38256
 
3.8%
r 35150
 
3.5%
Other values (11) 109648
11.0%
Uppercase Letter
ValueCountFrequency (%)
P 35585
35.6%
C 19414
19.4%
H 8933
 
8.9%
R 7786
 
7.8%
S 6385
 
6.4%
B 5880
 
5.9%
A 4034
 
4.0%
V 3764
 
3.8%
E 3171
 
3.2%
M 1597
 
1.6%
Other values (8) 3460
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1099690
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 142730
13.0%
d 138281
12.6%
a 122122
11.1%
i 111897
10.2%
o 103550
9.4%
t 74826
 
6.8%
l 66233
 
6.0%
n 56988
 
5.2%
h 38256
 
3.5%
P 35585
 
3.2%
Other values (29) 209222
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 142730
13.0%
d 138281
12.6%
a 122122
11.1%
i 111897
10.2%
o 103550
9.4%
t 74826
 
6.8%
l 66233
 
6.0%
n 56988
 
5.2%
h 38256
 
3.5%
P 35585
 
3.2%
Other values (29) 209222
19.0%

subtribe
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:10.816591image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters30
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPseudacris
2nd rowPseudacris
3rd rowPseudacris
ValueCountFrequency (%)
pseudacris 3
100.0%
2025-01-23T18:15:10.916280image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 6
20.0%
P 3
10.0%
e 3
10.0%
u 3
10.0%
d 3
10.0%
a 3
10.0%
c 3
10.0%
r 3
10.0%
i 3
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
90.0%
Uppercase Letter 3
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 6
22.2%
e 3
11.1%
u 3
11.1%
d 3
11.1%
a 3
11.1%
c 3
11.1%
r 3
11.1%
i 3
11.1%
Uppercase Letter
ValueCountFrequency (%)
P 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 6
20.0%
P 3
10.0%
e 3
10.0%
u 3
10.0%
d 3
10.0%
a 3
10.0%
c 3
10.0%
r 3
10.0%
i 3
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 6
20.0%
P 3
10.0%
e 3
10.0%
u 3
10.0%
d 3
10.0%
a 3
10.0%
c 3
10.0%
r 3
10.0%
i 3
10.0%

genus
Text

Distinct436
Distinct (%)0.4%
Missing36
Missing (%)< 0.1%
Memory size810.6 KiB
2025-01-23T18:15:11.109653image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length17
Mean length8.689048322
Min length3

Characters and Unicode

Total characters901063
Distinct characters50
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)0.1%

Sample

1st rowRhacophorus
2nd rowRana
3rd rowPlethodon
4th rowDesmognathus
5th rowLampropeltis
ValueCountFrequency (%)
desmognathus 12827
 
12.4%
plethodon 8408
 
8.1%
rana 6409
 
6.2%
bufo 5881
 
5.7%
eurycea 4979
 
4.8%
pseudotriton 3386
 
3.3%
acris 3010
 
2.9%
nerodia 3010
 
2.9%
pseudacris 3005
 
2.9%
notophthalmus 2888
 
2.8%
Other values (425) 49902
48.1%
2025-01-23T18:15:11.386497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 87491
 
9.7%
s 74581
 
8.3%
a 74361
 
8.3%
e 69994
 
7.8%
t 55328
 
6.1%
n 52118
 
5.8%
u 51497
 
5.7%
r 50703
 
5.6%
h 48239
 
5.4%
i 42615
 
4.7%
Other values (40) 294136
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 797354
88.5%
Uppercase Letter 103703
 
11.5%
Space Separator 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 87491
11.0%
s 74581
 
9.4%
a 74361
 
9.3%
e 69994
 
8.8%
t 55328
 
6.9%
n 52118
 
6.5%
u 51497
 
6.5%
r 50703
 
6.4%
h 48239
 
6.0%
i 42615
 
5.3%
Other values (15) 190427
23.9%
Uppercase Letter
ValueCountFrequency (%)
P 16508
15.9%
D 14249
13.7%
A 9861
9.5%
E 9616
9.3%
R 7406
7.1%
N 7334
7.1%
S 6302
 
6.1%
C 6131
 
5.9%
B 6023
 
5.8%
H 4809
 
4.6%
Other values (13) 15464
14.9%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 901057
> 99.9%
Common 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 87491
 
9.7%
s 74581
 
8.3%
a 74361
 
8.3%
e 69994
 
7.8%
t 55328
 
6.1%
n 52118
 
5.8%
u 51497
 
5.7%
r 50703
 
5.6%
h 48239
 
5.4%
i 42615
 
4.7%
Other values (38) 294130
32.6%
Common
ValueCountFrequency (%)
4
66.7%
. 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 901063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 87491
 
9.7%
s 74581
 
8.3%
a 74361
 
8.3%
e 69994
 
7.8%
t 55328
 
6.1%
n 52118
 
5.8%
u 51497
 
5.7%
r 50703
 
5.6%
h 48239
 
5.4%
i 42615
 
4.7%
Other values (40) 294136
32.6%

infragenericEpithet
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:11.444997image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowbrimleyi
2nd rowbrimleyi
3rd rowbrimleyi
ValueCountFrequency (%)
brimleyi 3
100.0%
2025-01-23T18:15:11.548104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 6
25.0%
b 3
12.5%
r 3
12.5%
m 3
12.5%
l 3
12.5%
e 3
12.5%
y 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 6
25.0%
b 3
12.5%
r 3
12.5%
m 3
12.5%
l 3
12.5%
e 3
12.5%
y 3
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 6
25.0%
b 3
12.5%
r 3
12.5%
m 3
12.5%
l 3
12.5%
e 3
12.5%
y 3
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 6
25.0%
b 3
12.5%
r 3
12.5%
m 3
12.5%
l 3
12.5%
e 3
12.5%
y 3
12.5%

specificEpithet
Text

Distinct1140
Distinct (%)1.1%
Missing65
Missing (%)0.1%
Memory size810.6 KiB
2025-01-23T18:15:11.740399image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length21
Mean length8.909917818
Min length3

Characters and Unicode

Total characters923709
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)0.3%

Sample

1st rowpachyproctus
2nd rowclamitans
3rd rowglutinosus
4th rowmonticola
5th rowtriangulum
ValueCountFrequency (%)
fuscus 3201
 
3.1%
viridescens 2884
 
2.8%
ruber 2605
 
2.5%
ocoee 2295
 
2.2%
monticola 2026
 
1.9%
punctatus 1892
 
1.8%
porphyriticus 1823
 
1.7%
sphenocephala 1752
 
1.7%
obsoleta 1743
 
1.7%
terrestris 1701
 
1.6%
Other values (1072) 82634
79.0%
2025-01-23T18:15:12.005733image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 99604
10.8%
i 90957
9.8%
s 87151
9.4%
r 79322
8.6%
e 75044
 
8.1%
t 67874
 
7.3%
u 61806
 
6.7%
c 61802
 
6.7%
o 55300
 
6.0%
n 49337
 
5.3%
Other values (21) 195512
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 920873
99.7%
Other Punctuation 1951
 
0.2%
Space Separator 885
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 99604
10.8%
i 90957
9.9%
s 87151
9.5%
r 79322
8.6%
e 75044
 
8.1%
t 67874
 
7.4%
u 61806
 
6.7%
c 61802
 
6.7%
o 55300
 
6.0%
n 49337
 
5.4%
Other values (16) 192676
20.9%
Other Punctuation
ValueCountFrequency (%)
. 1940
99.4%
? 10
 
0.5%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
884
99.9%
  1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 920873
99.7%
Common 2836
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 99604
10.8%
i 90957
9.9%
s 87151
9.5%
r 79322
8.6%
e 75044
 
8.1%
t 67874
 
7.4%
u 61806
 
6.7%
c 61802
 
6.7%
o 55300
 
6.0%
n 49337
 
5.4%
Other values (16) 192676
20.9%
Common
ValueCountFrequency (%)
. 1940
68.4%
884
31.2%
? 10
 
0.4%
  1
 
< 0.1%
/ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 923708
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 99604
10.8%
i 90957
9.8%
s 87151
9.4%
r 79322
8.6%
e 75044
 
8.1%
t 67874
 
7.3%
u 61806
 
6.7%
c 61802
 
6.7%
o 55300
 
6.0%
n 49337
 
5.3%
Other values (20) 195511
21.2%
None
ValueCountFrequency (%)
  1
100.0%

infraspecificEpithet
Text

Missing 

Distinct267
Distinct (%)7.3%
Missing100055
Missing (%)96.5%
Memory size810.6 KiB
2025-01-23T18:15:12.170682image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.543997827
Min length4

Characters and Unicode

Total characters35141
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)2.1%

Sample

1st rowelapsoides
2nd rowterrestris
3rd rowpiscivorus
4th rowpiscivorus
5th rowminor
ValueCountFrequency (%)
americanus 452
 
11.7%
dorsalis 393
 
10.2%
piscivorus 354
 
9.2%
rhombomaculata 263
 
6.8%
cf 134
 
3.5%
williamengelsi 114
 
3.0%
elapsoides 112
 
2.9%
elegans 107
 
2.8%
feriarum 88
 
2.3%
floridana 82
 
2.1%
Other values (247) 1759
45.6%
2025-01-23T18:15:12.406145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4321
12.3%
i 4018
11.4%
s 3797
10.8%
r 2789
 
7.9%
o 2219
 
6.3%
e 2211
 
6.3%
u 2142
 
6.1%
l 2140
 
6.1%
c 1960
 
5.6%
n 1599
 
4.6%
Other values (20) 7945
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34819
99.1%
Space Separator 176
 
0.5%
Other Punctuation 144
 
0.4%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4321
12.4%
i 4018
11.5%
s 3797
10.9%
r 2789
 
8.0%
o 2219
 
6.4%
e 2211
 
6.3%
u 2142
 
6.2%
l 2140
 
6.1%
c 1960
 
5.6%
n 1599
 
4.6%
Other values (16) 7623
21.9%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Punctuation
ValueCountFrequency (%)
. 144
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34819
99.1%
Common 322
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4321
12.4%
i 4018
11.5%
s 3797
10.9%
r 2789
 
8.0%
o 2219
 
6.4%
e 2211
 
6.3%
u 2142
 
6.2%
l 2140
 
6.1%
c 1960
 
5.6%
n 1599
 
4.6%
Other values (16) 7623
21.9%
Common
ValueCountFrequency (%)
176
54.7%
. 144
44.7%
[ 1
 
0.3%
] 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4321
12.3%
i 4018
11.4%
s 3797
10.8%
r 2789
 
7.9%
o 2219
 
6.3%
e 2211
 
6.3%
u 2142
 
6.1%
l 2140
 
6.1%
c 1960
 
5.6%
n 1599
 
4.6%
Other values (20) 7945
22.6%

cultivarEpithet
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:12.573718image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters45
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspecificEpithet
2nd rowspecificEpithet
3rd rowspecificEpithet
ValueCountFrequency (%)
specificepithet 3
100.0%
2025-01-23T18:15:12.676161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 9
20.0%
p 6
13.3%
e 6
13.3%
c 6
13.3%
t 6
13.3%
s 3
 
6.7%
f 3
 
6.7%
E 3
 
6.7%
h 3
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42
93.3%
Uppercase Letter 3
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 9
21.4%
p 6
14.3%
e 6
14.3%
c 6
14.3%
t 6
14.3%
s 3
 
7.1%
f 3
 
7.1%
h 3
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 9
20.0%
p 6
13.3%
e 6
13.3%
c 6
13.3%
t 6
13.3%
s 3
 
6.7%
f 3
 
6.7%
E 3
 
6.7%
h 3
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 9
20.0%
p 6
13.3%
e 6
13.3%
c 6
13.3%
t 6
13.3%
s 3
 
6.7%
f 3
 
6.7%
E 3
 
6.7%
h 3
 
6.7%

taxonRank
Text

Distinct3
Distinct (%)< 0.1%
Missing36
Missing (%)< 0.1%
Memory size810.6 KiB
2025-01-23T18:15:12.727851image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length15
Mean length15.17473313
Min length5

Characters and Unicode

Total characters1573635
Distinct characters14
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspecificEpithet
2nd rowspecificEpithet
3rd rowspecificEpithet
4th rowspecificEpithet
5th rowinfraspecificEpithet
ValueCountFrequency (%)
specificepithet 99990
96.4%
infraspecificepithet 3682
 
3.6%
genus 29
 
< 0.1%
2025-01-23T18:15:12.847338image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 314698
20.0%
e 207373
13.2%
p 207344
13.2%
c 207344
13.2%
t 207344
13.2%
f 107354
 
6.8%
s 103701
 
6.6%
E 103672
 
6.6%
h 103672
 
6.6%
n 3711
 
0.2%
Other values (4) 7422
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1469934
93.4%
Uppercase Letter 103701
 
6.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 314698
21.4%
e 207373
14.1%
p 207344
14.1%
c 207344
14.1%
t 207344
14.1%
f 107354
 
7.3%
s 103701
 
7.1%
h 103672
 
7.1%
n 3711
 
0.3%
r 3682
 
0.3%
Other values (2) 3711
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
E 103672
> 99.9%
G 29
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1573635
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 314698
20.0%
e 207373
13.2%
p 207344
13.2%
c 207344
13.2%
t 207344
13.2%
f 107354
 
6.8%
s 103701
 
6.6%
E 103672
 
6.6%
h 103672
 
6.6%
n 3711
 
0.2%
Other values (4) 7422
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1573635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 314698
20.0%
e 207373
13.2%
p 207344
13.2%
c 207344
13.2%
t 207344
13.2%
f 107354
 
6.8%
s 103701
 
6.6%
E 103672
 
6.6%
h 103672
 
6.6%
n 3711
 
0.2%
Other values (4) 7422
 
0.5%

scientificNameAuthorship
Text

Constant  Missing 

Distinct1
Distinct (%)33.3%
Missing103734
Missing (%)> 99.9%
Memory size810.6 KiB
2025-01-23T18:15:12.895977image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters63
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBrimley's Chorus Frog
2nd rowBrimley's Chorus Frog
3rd rowBrimley's Chorus Frog
ValueCountFrequency (%)
brimley's 3
33.3%
chorus 3
33.3%
frog 3
33.3%
2025-01-23T18:15:13.000486image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 9
14.3%
s 6
 
9.5%
6
 
9.5%
o 6
 
9.5%
B 3
 
4.8%
i 3
 
4.8%
m 3
 
4.8%
l 3
 
4.8%
e 3
 
4.8%
y 3
 
4.8%
Other values (6) 18
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45
71.4%
Uppercase Letter 9
 
14.3%
Space Separator 6
 
9.5%
Other Punctuation 3
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 9
20.0%
s 6
13.3%
o 6
13.3%
i 3
 
6.7%
m 3
 
6.7%
l 3
 
6.7%
e 3
 
6.7%
y 3
 
6.7%
h 3
 
6.7%
u 3
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
C 3
33.3%
F 3
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
' 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54
85.7%
Common 9
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 9
16.7%
s 6
11.1%
o 6
11.1%
B 3
 
5.6%
i 3
 
5.6%
m 3
 
5.6%
l 3
 
5.6%
e 3
 
5.6%
y 3
 
5.6%
C 3
 
5.6%
Other values (4) 12
22.2%
Common
ValueCountFrequency (%)
6
66.7%
' 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 9
14.3%
s 6
 
9.5%
6
 
9.5%
o 6
 
9.5%
B 3
 
4.8%
i 3
 
4.8%
m 3
 
4.8%
l 3
 
4.8%
e 3
 
4.8%
y 3
 
4.8%
Other values (6) 18
28.6%

vernacularName
Text

Missing 

Distinct966
Distinct (%)1.0%
Missing10563
Missing (%)10.2%
Memory size810.6 KiB
2025-01-23T18:15:13.190466image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length105
Median length75
Mean length18.33543692
Min length5

Characters and Unicode

Total characters1708386
Distinct characters66
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)0.3%

Sample

1st rowGreen Frog
2nd rowNorthern Slimy Salamander
3rd rowScarlet Kingsnake
4th rowSlider
5th rowBog Turtle
ValueCountFrequency (%)
salamander 32427
 
14.0%
snake 15601
 
6.7%
frog 11255
 
4.9%
eastern 8872
 
3.8%
southern 8701
 
3.8%
dusky 7873
 
3.4%
toad 6900
 
3.0%
northern 6216
 
2.7%
turtle 4159
 
1.8%
green 3600
 
1.6%
Other values (803) 126364
54.5%
2025-01-23T18:15:13.472744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 192355
 
11.3%
a 184837
 
10.8%
r 144761
 
8.5%
138801
 
8.1%
n 124084
 
7.3%
o 89193
 
5.2%
d 76160
 
4.5%
l 75540
 
4.4%
S 74908
 
4.4%
t 67872
 
4.0%
Other values (56) 539875
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1323190
77.5%
Uppercase Letter 231648
 
13.6%
Space Separator 138801
 
8.1%
Dash Punctuation 10115
 
0.6%
Other Punctuation 4530
 
0.3%
Final Punctuation 35
 
< 0.1%
Close Punctuation 31
 
< 0.1%
Open Punctuation 31
 
< 0.1%
Other Letter 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 192355
14.5%
a 184837
14.0%
r 144761
10.9%
n 124084
9.4%
o 89193
 
6.7%
d 76160
 
5.8%
l 75540
 
5.7%
t 67872
 
5.1%
i 47491
 
3.6%
m 47380
 
3.6%
Other values (16) 273517
20.7%
Uppercase Letter
ValueCountFrequency (%)
S 74908
32.3%
T 20114
 
8.7%
R 16586
 
7.2%
F 15975
 
6.9%
C 15236
 
6.6%
N 10450
 
4.5%
B 10442
 
4.5%
D 10319
 
4.5%
E 10046
 
4.3%
G 9560
 
4.1%
Other values (15) 38012
16.4%
Other Punctuation
ValueCountFrequency (%)
' 3660
80.8%
, 845
 
18.7%
/ 20
 
0.4%
; 4
 
0.1%
: 1
 
< 0.1%
Other Letter
ValueCountFrequency (%)
日 1
20.0%
本 1
20.0%
語 1
20.0%
ハ 1
20.0%
ブ 1
20.0%
Space Separator
ValueCountFrequency (%)
138801
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10115
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1554838
91.0%
Common 153543
 
9.0%
Han 3
 
< 0.1%
Katakana 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 192355
12.4%
a 184837
 
11.9%
r 144761
 
9.3%
n 124084
 
8.0%
o 89193
 
5.7%
d 76160
 
4.9%
l 75540
 
4.9%
S 74908
 
4.8%
t 67872
 
4.4%
i 47491
 
3.1%
Other values (41) 477637
30.7%
Common
ValueCountFrequency (%)
138801
90.4%
- 10115
 
6.6%
' 3660
 
2.4%
, 845
 
0.6%
’ 35
 
< 0.1%
) 31
 
< 0.1%
( 31
 
< 0.1%
/ 20
 
< 0.1%
; 4
 
< 0.1%
: 1
 
< 0.1%
Han
ValueCountFrequency (%)
日 1
33.3%
本 1
33.3%
語 1
33.3%
Katakana
ValueCountFrequency (%)
ハ 1
50.0%
ブ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1708346
> 99.9%
Punctuation 35
 
< 0.1%
CJK 3
 
< 0.1%
Katakana 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 192355
 
11.3%
a 184837
 
10.8%
r 144761
 
8.5%
138801
 
8.1%
n 124084
 
7.3%
o 89193
 
5.2%
d 76160
 
4.5%
l 75540
 
4.4%
S 74908
 
4.4%
t 67872
 
4.0%
Other values (50) 539835
31.6%
Punctuation
ValueCountFrequency (%)
’ 35
100.0%
CJK
ValueCountFrequency (%)
日 1
33.3%
本 1
33.3%
語 1
33.3%
Katakana
ValueCountFrequency (%)
ハ 1
50.0%
ブ 1
50.0%